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July 25, 2016 18:25
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| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally | |
| WARNING:tensorflow:<tensorflow.python.ops.rnn_cell.BasicLSTMCell object at 0x7fe3fc03dd10>: Using a concatenated state is slower and will soon be deprecated. Use state_is_tuple=True. | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties: | |
| name: Tesla K40c | |
| major: 3 minor: 5 memoryClockRate (GHz) 0.745 | |
| pciBusID 0000:88:00.0 | |
| Total memory: 12.00GiB | |
| Free memory: 11.90GiB | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0 | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y | |
| I tensorflow/core/common_runtime/gpu/gpu_device.cc:806] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K40c, pci bus id: 0000:88:00.0) | |
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| /home/ronghang/anaconda/lib/python2.7/site-packages/skimage/util/dtype.py:110: UserWarning: Possible precision loss when converting from float64 to uint8 | |
| "%s to %s" % (dtypeobj_in, dtypeobj)) | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 16.19GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 32.38GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 32.38GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 16.29GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 32.57GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 32.57GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
| W tensorflow/core/common_runtime/bfc_allocator.cc:213] Ran out of memory trying to allocate 17.39GiB. The caller indicates that this is not a failure, but may mean that there could be performance gains if more memory is available. | |
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| Final results on the whole test set | |
| [email protected] = 0.336128 | |
| [email protected] = 0.266534 | |
| [email protected] = 0.191731 | |
| [email protected] = 0.117461 | |
| [email protected] = 0.042309 | |
| overall IoU = 0.479988 |
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| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcublas.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcudnn.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcufft.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcuda.so locally | |
| I tensorflow/stream_executor/dso_loader.cc:108] successfully opened CUDA library libcurand.so locally | |
| WARNING:tensorflow:<tensorflow.python.ops.rnn_cell.BasicLSTMCell object at 0x7fb34405be50>: Using a concatenated state is slower and will soon be deprecated. Use state_is_tuple=True. | |
| Collecting variables to train: | |
| word_embedding/embedding:0 | |
| lstm_lang/RNN/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix:0 | |
| lstm_lang/RNN/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias:0 | |
| classifier/mlp_l1/weights:0 | |
| classifier/mlp_l1/biases:0 | |
| classifier/mlp_l2/weights:0 | |
| classifier/mlp_l2/biases:0 | |
| Done. | |
| Collecting variables for regularization: | |
| lstm_lang/RNN/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix:0 | |
| classifier/mlp_l1/weights:0 | |
| classifier/mlp_l2/weights:0 | |
| Done. | |
| Variable learning rate multiplication: | |
| word_embedding/embedding:0: 1.000000 | |
| lstm_lang/RNN/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Matrix:0: 1.000000 | |
| lstm_lang/RNN/MultiRNNCell/Cell0/BasicLSTMCell/Linear/Bias:0: 1.000000 | |
| classifier/mlp_l1/weights:0: 1.000000 | |
| classifier/mlp_l1/biases:0: 1.000000 | |
| classifier/mlp_l2/weights:0: 1.000000 | |
| classifier/mlp_l2/biases:0: 1.000000 | |
| Done. | |
| found 4040 batches under ./exp-referit/data/train_batch_det/ with prefix "referit_train_det" | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:102] Found device 0 with properties: | |
| name: Tesla K40c | |
| major: 3 minor: 5 memoryClockRate (GHz) 0.745 | |
| pciBusID 0000:88:00.0 | |
| Total memory: 12.00GiB | |
| Free memory: 11.90GiB | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:126] DMA: 0 | |
| I tensorflow/core/common_runtime/gpu/gpu_init.cc:136] 0: Y | |
| I tensorflow/core/common_runtime/gpu/gpu_device.cc:806] Creating TensorFlow device (/gpu:0) -> (device: 0, name: Tesla K40c, pci bus id: 0000:88:00.0) | |
| data reader: epoch = 0, batch = 0 / 4040 | |
| iter = 0, cls_loss (cur) = 0.704010, cls_loss (avg) = 0.007040, lr = 0.010000 | |
| iter = 0, accuracy (cur) = 0.420000 (all), 1.000000 (pos), 0.000000 (neg) | |
| iter = 0, accuracy (avg) = 0.004200 (all), 0.010000 (pos), 0.000000 (neg) | |
| data reader: epoch = 0, batch = 1 / 4040 | |
| iter = 1, cls_loss (cur) = 0.708250, cls_loss (avg) = 0.014052, lr = 0.010000 | |
| iter = 1, accuracy (cur) = 0.420000 (all), 0.093750 (pos), 1.000000 (neg) | |
| iter = 1, accuracy (avg) = 0.008358 (all), 0.010838 (pos), 0.010000 (neg) | |
| data reader: epoch = 0, batch = 2 / 4040 | |
| I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 1803 get requests, put_count=1696 evicted_count=1000 eviction_rate=0.589623 and unsatisfied allocation rate=0.66944 | |
| I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 100 to 110 | |
| iter = 2, cls_loss (cur) = 0.682844, cls_loss (avg) = 0.020740, lr = 0.010000 | |
| iter = 2, accuracy (cur) = 0.540000 (all), 0.533333 (pos), 0.550000 (neg) | |
| iter = 2, accuracy (avg) = 0.013674 (all), 0.016062 (pos), 0.015400 (neg) | |
| data reader: epoch = 0, batch = 3 / 4040 | |
| iter = 3, cls_loss (cur) = 0.671874, cls_loss (avg) = 0.027251, lr = 0.010000 | |
| iter = 3, accuracy (cur) = 0.540000 (all), 0.807692 (pos), 0.250000 (neg) | |
| iter = 3, accuracy (avg) = 0.018938 (all), 0.023979 (pos), 0.017746 (neg) | |
| data reader: epoch = 0, batch = 4 / 4040 | |
| iter = 4, cls_loss (cur) = 0.664269, cls_loss (avg) = 0.033622, lr = 0.010000 | |
| iter = 4, accuracy (cur) = 0.580000 (all), 0.923077 (pos), 0.208333 (neg) | |
| iter = 4, accuracy (avg) = 0.024548 (all), 0.032970 (pos), 0.019652 (neg) | |
| data reader: epoch = 0, batch = 5 / 4040 | |
| iter = 5, cls_loss (cur) = 0.693595, cls_loss (avg) = 0.040221, lr = 0.010000 | |
| iter = 5, accuracy (cur) = 0.560000 (all), 0.947368 (pos), 0.322581 (neg) | |
| iter = 5, accuracy (avg) = 0.029903 (all), 0.042114 (pos), 0.022681 (neg) | |
| data reader: epoch = 0, batch = 6 / 4040 | |
| iter = 6, cls_loss (cur) = 0.626969, cls_loss (avg) = 0.046089, lr = 0.010000 | |
| iter = 6, accuracy (cur) = 0.720000 (all), 0.807692 (pos), 0.625000 (neg) | |
| iter = 6, accuracy (avg) = 0.036804 (all), 0.049770 (pos), 0.028704 (neg) | |
| data reader: epoch = 0, batch = 7 / 4040 | |
| iter = 7, cls_loss (cur) = 0.677577, cls_loss (avg) = 0.052404, lr = 0.010000 | |
| iter = 7, accuracy (cur) = 0.540000 (all), 0.695652 (pos), 0.407407 (neg) | |
| iter = 7, accuracy (avg) = 0.041836 (all), 0.056228 (pos), 0.032491 (neg) | |
| data reader: epoch = 0, batch = 8 / 4040 | |
| iter = 8, cls_loss (cur) = 0.655785, cls_loss (avg) = 0.058438, lr = 0.010000 | |
| iter = 8, accuracy (cur) = 0.720000 (all), 0.727273 (pos), 0.714286 (neg) | |
| iter = 8, accuracy (avg) = 0.048617 (all), 0.062939 (pos), 0.039309 (neg) | |
| data reader: epoch = 0, batch = 9 / 4040 | |
| iter = 9, cls_loss (cur) = 0.614681, cls_loss (avg) = 0.064000, lr = 0.010000 | |
| iter = 9, accuracy (cur) = 0.820000 (all), 0.703704 (pos), 0.956522 (neg) | |
| iter = 9, accuracy (avg) = 0.056331 (all), 0.069346 (pos), 0.048481 (neg) | |
| data reader: epoch = 0, batch = 10 / 4040 | |
| iter = 10, cls_loss (cur) = 0.679452, cls_loss (avg) = 0.070154, lr = 0.010000 | |
| iter = 10, accuracy (cur) = 0.580000 (all), 0.500000 (pos), 0.653846 (neg) | |
| iter = 10, accuracy (avg) = 0.061568 (all), 0.073653 (pos), 0.054535 (neg) | |
| data reader: epoch = 0, batch = 11 / 4040 | |
| iter = 11, cls_loss (cur) = 0.638077, cls_loss (avg) = 0.075834, lr = 0.010000 | |
| iter = 11, accuracy (cur) = 0.660000 (all), 0.666667 (pos), 0.653846 (neg) | |
| iter = 11, accuracy (avg) = 0.067552 (all), 0.079583 (pos), 0.060528 (neg) | |
| data reader: epoch = 0, batch = 12 / 4040 | |
| iter = 12, cls_loss (cur) = 0.633346, cls_loss (avg) = 0.081409, lr = 0.010000 | |
| iter = 12, accuracy (cur) = 0.720000 (all), 0.642857 (pos), 0.818182 (neg) | |
| iter = 12, accuracy (avg) = 0.074077 (all), 0.085216 (pos), 0.068105 (neg) | |
| data reader: epoch = 0, batch = 13 / 4040 | |
| iter = 13, cls_loss (cur) = 0.640836, cls_loss (avg) = 0.087003, lr = 0.010000 | |
| iter = 13, accuracy (cur) = 0.700000 (all), 0.620690 (pos), 0.809524 (neg) | |
| iter = 13, accuracy (avg) = 0.080336 (all), 0.090571 (pos), 0.075519 (neg) | |
| data reader: epoch = 0, batch = 14 / 4040 | |
| iter = 14, cls_loss (cur) = 0.652784, cls_loss (avg) = 0.092661, lr = 0.010000 | |
| iter = 14, accuracy (cur) = 0.660000 (all), 0.583333 (pos), 0.730769 (neg) | |
| iter = 14, accuracy (avg) = 0.086133 (all), 0.095498 (pos), 0.082071 (neg) | |
| data reader: epoch = 0, batch = 15 / 4040 | |
| iter = 15, cls_loss (cur) = 0.631273, cls_loss (avg) = 0.098047, lr = 0.010000 | |
| iter = 15, accuracy (cur) = 0.640000 (all), 0.615385 (pos), 0.666667 (neg) | |
| iter = 15, accuracy (avg) = 0.091671 (all), 0.100697 (pos), 0.087917 (neg) | |
| data reader: epoch = 0, batch = 16 / 4040 | |
| iter = 16, cls_loss (cur) = 0.578116, cls_loss (avg) = 0.102848, lr = 0.010000 | |
| iter = 16, accuracy (cur) = 0.780000 (all), 0.909091 (pos), 0.678571 (neg) | |
| iter = 16, accuracy (avg) = 0.098555 (all), 0.108781 (pos), 0.093824 (neg) | |
| data reader: epoch = 0, batch = 17 / 4040 | |
| iter = 17, cls_loss (cur) = 0.618522, cls_loss (avg) = 0.108004, lr = 0.010000 | |
| iter = 17, accuracy (cur) = 0.680000 (all), 0.761905 (pos), 0.620690 (neg) | |
| iter = 17, accuracy (avg) = 0.104369 (all), 0.115312 (pos), 0.099093 (neg) | |
| data reader: epoch = 0, batch = 18 / 4040 | |
| iter = 18, cls_loss (cur) = 0.652371, cls_loss (avg) = 0.113448, lr = 0.010000 | |
| iter = 18, accuracy (cur) = 0.620000 (all), 0.733333 (pos), 0.571429 (neg) | |
| iter = 18, accuracy (avg) = 0.109525 (all), 0.121492 (pos), 0.103816 (neg) | |
| data reader: epoch = 0, batch = 19 / 4040 | |
| iter = 19, cls_loss (cur) = 0.644488, cls_loss (avg) = 0.118759, lr = 0.010000 | |
| iter = 19, accuracy (cur) = 0.680000 (all), 0.600000 (pos), 0.733333 (neg) | |
| iter = 19, accuracy (avg) = 0.115230 (all), 0.126278 (pos), 0.110111 (neg) | |
| data reader: epoch = 0, batch = 20 / 4040 | |
| iter = 20, cls_loss (cur) = 0.618447, cls_loss (avg) = 0.123755, lr = 0.010000 | |
| iter = 20, accuracy (cur) = 0.660000 (all), 0.520000 (pos), 0.800000 (neg) | |
| iter = 20, accuracy (avg) = 0.120678 (all), 0.130215 (pos), 0.117010 (neg) | |
| data reader: epoch = 0, batch = 21 / 4040 | |
| iter = 21, cls_loss (cur) = 0.607834, cls_loss (avg) = 0.128596, lr = 0.010000 | |
| iter = 21, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 21, accuracy (avg) = 0.127071 (all), 0.135313 (pos), 0.124640 (neg) | |
| data reader: epoch = 0, batch = 22 / 4040 | |
| iter = 22, cls_loss (cur) = 0.628391, cls_loss (avg) = 0.133594, lr = 0.010000 | |
| iter = 22, accuracy (cur) = 0.660000 (all), 0.520000 (pos), 0.800000 (neg) | |
| iter = 22, accuracy (avg) = 0.132400 (all), 0.139159 (pos), 0.131394 (neg) | |
| data reader: epoch = 0, batch = 23 / 4040 | |
| iter = 23, cls_loss (cur) = 0.643117, cls_loss (avg) = 0.138689, lr = 0.010000 | |
| iter = 23, accuracy (cur) = 0.640000 (all), 0.478261 (pos), 0.777778 (neg) | |
| iter = 23, accuracy (avg) = 0.137476 (all), 0.142551 (pos), 0.137857 (neg) | |
| data reader: epoch = 0, batch = 24 / 4040 | |
| iter = 24, cls_loss (cur) = 0.600247, cls_loss (avg) = 0.143305, lr = 0.010000 | |
| iter = 24, accuracy (cur) = 0.740000 (all), 0.500000 (pos), 0.961538 (neg) | |
| iter = 24, accuracy (avg) = 0.143501 (all), 0.146125 (pos), 0.146094 (neg) | |
| data reader: epoch = 0, batch = 25 / 4040 | |
| iter = 25, cls_loss (cur) = 0.595782, cls_loss (avg) = 0.147830, lr = 0.010000 | |
| iter = 25, accuracy (cur) = 0.700000 (all), 0.352941 (pos), 0.878788 (neg) | |
| iter = 25, accuracy (avg) = 0.149066 (all), 0.148193 (pos), 0.153421 (neg) | |
| data reader: epoch = 0, batch = 26 / 4040 | |
| iter = 26, cls_loss (cur) = 0.610449, cls_loss (avg) = 0.152456, lr = 0.010000 | |
| iter = 26, accuracy (cur) = 0.680000 (all), 0.423077 (pos), 0.958333 (neg) | |
| iter = 26, accuracy (avg) = 0.154376 (all), 0.150942 (pos), 0.161470 (neg) | |
| data reader: epoch = 0, batch = 27 / 4040 | |
| iter = 27, cls_loss (cur) = 0.609338, cls_loss (avg) = 0.157025, lr = 0.010000 | |
| iter = 27, accuracy (cur) = 0.640000 (all), 0.400000 (pos), 0.880000 (neg) | |
| iter = 27, accuracy (avg) = 0.159232 (all), 0.153433 (pos), 0.168656 (neg) | |
| data reader: epoch = 0, batch = 28 / 4040 | |
| iter = 28, cls_loss (cur) = 0.638276, cls_loss (avg) = 0.161837, lr = 0.010000 | |
| iter = 28, accuracy (cur) = 0.620000 (all), 0.428571 (pos), 0.863636 (neg) | |
| iter = 28, accuracy (avg) = 0.163840 (all), 0.156184 (pos), 0.175605 (neg) | |
| data reader: epoch = 0, batch = 29 / 4040 | |
| iter = 29, cls_loss (cur) = 0.619102, cls_loss (avg) = 0.166410, lr = 0.010000 | |
| iter = 29, accuracy (cur) = 0.620000 (all), 0.551724 (pos), 0.714286 (neg) | |
| iter = 29, accuracy (avg) = 0.168401 (all), 0.160139 (pos), 0.180992 (neg) | |
| data reader: epoch = 0, batch = 30 / 4040 | |
| iter = 30, cls_loss (cur) = 0.579502, cls_loss (avg) = 0.170541, lr = 0.010000 | |
| iter = 30, accuracy (cur) = 0.680000 (all), 0.615385 (pos), 0.750000 (neg) | |
| iter = 30, accuracy (avg) = 0.173517 (all), 0.164692 (pos), 0.186682 (neg) | |
| data reader: epoch = 0, batch = 31 / 4040 | |
| iter = 31, cls_loss (cur) = 0.521728, cls_loss (avg) = 0.174053, lr = 0.010000 | |
| iter = 31, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 31, accuracy (avg) = 0.179782 (all), 0.171045 (pos), 0.192815 (neg) | |
| data reader: epoch = 0, batch = 32 / 4040 | |
| iter = 32, cls_loss (cur) = 0.565409, cls_loss (avg) = 0.177966, lr = 0.010000 | |
| iter = 32, accuracy (cur) = 0.740000 (all), 0.809524 (pos), 0.689655 (neg) | |
| iter = 32, accuracy (avg) = 0.185384 (all), 0.177430 (pos), 0.197784 (neg) | |
| data reader: epoch = 0, batch = 33 / 4040 | |
| iter = 33, cls_loss (cur) = 0.597874, cls_loss (avg) = 0.182165, lr = 0.010000 | |
| iter = 33, accuracy (cur) = 0.720000 (all), 0.700000 (pos), 0.733333 (neg) | |
| iter = 33, accuracy (avg) = 0.190730 (all), 0.182655 (pos), 0.203139 (neg) | |
| data reader: epoch = 0, batch = 34 / 4040 | |
| iter = 34, cls_loss (cur) = 0.639726, cls_loss (avg) = 0.186741, lr = 0.010000 | |
| iter = 34, accuracy (cur) = 0.520000 (all), 0.518519 (pos), 0.521739 (neg) | |
| iter = 34, accuracy (avg) = 0.194023 (all), 0.186014 (pos), 0.206325 (neg) | |
| data reader: epoch = 0, batch = 35 / 4040 | |
| iter = 35, cls_loss (cur) = 0.727502, cls_loss (avg) = 0.192149, lr = 0.010000 | |
| iter = 35, accuracy (cur) = 0.540000 (all), 0.529412 (pos), 0.545455 (neg) | |
| iter = 35, accuracy (avg) = 0.197483 (all), 0.189448 (pos), 0.209717 (neg) | |
| data reader: epoch = 0, batch = 36 / 4040 | |
| iter = 36, cls_loss (cur) = 0.626897, cls_loss (avg) = 0.196496, lr = 0.010000 | |
| iter = 36, accuracy (cur) = 0.620000 (all), 0.541667 (pos), 0.692308 (neg) | |
| iter = 36, accuracy (avg) = 0.201708 (all), 0.192970 (pos), 0.214542 (neg) | |
| data reader: epoch = 0, batch = 37 / 4040 | |
| I tensorflow/core/common_runtime/gpu/pool_allocator.cc:244] PoolAllocator: After 2404 get requests, put_count=2574 evicted_count=1000 eviction_rate=0.3885 and unsatisfied allocation rate=0.354825 | |
| I tensorflow/core/common_runtime/gpu/pool_allocator.cc:256] Raising pool_size_limit_ from 256 to 281 | |
| iter = 37, cls_loss (cur) = 0.595828, cls_loss (avg) = 0.200489, lr = 0.010000 | |
| iter = 37, accuracy (cur) = 0.740000 (all), 0.600000 (pos), 0.833333 (neg) | |
| iter = 37, accuracy (avg) = 0.207091 (all), 0.197040 (pos), 0.220730 (neg) | |
| data reader: epoch = 0, batch = 38 / 4040 | |
| iter = 38, cls_loss (cur) = 0.645895, cls_loss (avg) = 0.204943, lr = 0.010000 | |
| iter = 38, accuracy (cur) = 0.580000 (all), 0.483871 (pos), 0.736842 (neg) | |
| iter = 38, accuracy (avg) = 0.210820 (all), 0.199909 (pos), 0.225892 (neg) | |
| data reader: epoch = 0, batch = 39 / 4040 | |
| iter = 39, cls_loss (cur) = 0.627620, cls_loss (avg) = 0.209170, lr = 0.010000 | |
| iter = 39, accuracy (cur) = 0.600000 (all), 0.347826 (pos), 0.814815 (neg) | |
| iter = 39, accuracy (avg) = 0.214712 (all), 0.201388 (pos), 0.231781 (neg) | |
| data reader: epoch = 0, batch = 40 / 4040 | |
| iter = 40, cls_loss (cur) = 0.644449, cls_loss (avg) = 0.213523, lr = 0.010000 | |
| iter = 40, accuracy (cur) = 0.660000 (all), 0.500000 (pos), 0.944444 (neg) | |
| iter = 40, accuracy (avg) = 0.219165 (all), 0.204374 (pos), 0.238907 (neg) | |
| data reader: epoch = 0, batch = 41 / 4040 | |
| iter = 41, cls_loss (cur) = 0.563158, cls_loss (avg) = 0.217019, lr = 0.010000 | |
| iter = 41, accuracy (cur) = 0.700000 (all), 0.705882 (pos), 0.696970 (neg) | |
| iter = 41, accuracy (avg) = 0.223973 (all), 0.209389 (pos), 0.243488 (neg) | |
| data reader: epoch = 0, batch = 42 / 4040 | |
| iter = 42, cls_loss (cur) = 0.588427, cls_loss (avg) = 0.220733, lr = 0.010000 | |
| iter = 42, accuracy (cur) = 0.660000 (all), 0.480000 (pos), 0.840000 (neg) | |
| iter = 42, accuracy (avg) = 0.228333 (all), 0.212095 (pos), 0.249453 (neg) | |
| data reader: epoch = 0, batch = 43 / 4040 | |
| iter = 43, cls_loss (cur) = 0.594174, cls_loss (avg) = 0.224468, lr = 0.010000 | |
| iter = 43, accuracy (cur) = 0.620000 (all), 0.583333 (pos), 0.653846 (neg) | |
| iter = 43, accuracy (avg) = 0.232250 (all), 0.215808 (pos), 0.253497 (neg) | |
| data reader: epoch = 0, batch = 44 / 4040 | |
| iter = 44, cls_loss (cur) = 0.576101, cls_loss (avg) = 0.227984, lr = 0.010000 | |
| iter = 44, accuracy (cur) = 0.680000 (all), 0.558824 (pos), 0.937500 (neg) | |
| iter = 44, accuracy (avg) = 0.236728 (all), 0.219238 (pos), 0.260337 (neg) | |
| data reader: epoch = 0, batch = 45 / 4040 | |
| iter = 45, cls_loss (cur) = 0.523912, cls_loss (avg) = 0.230943, lr = 0.010000 | |
| iter = 45, accuracy (cur) = 0.760000 (all), 0.625000 (pos), 0.884615 (neg) | |
| iter = 45, accuracy (avg) = 0.241960 (all), 0.223295 (pos), 0.266580 (neg) | |
| data reader: epoch = 0, batch = 46 / 4040 | |
| iter = 46, cls_loss (cur) = 0.650453, cls_loss (avg) = 0.235139, lr = 0.010000 | |
| iter = 46, accuracy (cur) = 0.620000 (all), 0.571429 (pos), 0.655172 (neg) | |
| iter = 46, accuracy (avg) = 0.245741 (all), 0.226777 (pos), 0.270466 (neg) | |
| data reader: epoch = 0, batch = 47 / 4040 | |
| iter = 47, cls_loss (cur) = 0.524790, cls_loss (avg) = 0.238035, lr = 0.010000 | |
| iter = 47, accuracy (cur) = 0.780000 (all), 0.769231 (pos), 0.791667 (neg) | |
| iter = 47, accuracy (avg) = 0.251083 (all), 0.232201 (pos), 0.275678 (neg) | |
| data reader: epoch = 0, batch = 48 / 4040 | |
| iter = 48, cls_loss (cur) = 0.578643, cls_loss (avg) = 0.241441, lr = 0.010000 | |
| iter = 48, accuracy (cur) = 0.700000 (all), 0.636364 (pos), 0.750000 (neg) | |
| iter = 48, accuracy (avg) = 0.255572 (all), 0.236243 (pos), 0.280421 (neg) | |
| data reader: epoch = 0, batch = 49 / 4040 | |
| iter = 49, cls_loss (cur) = 0.621666, cls_loss (avg) = 0.245243, lr = 0.010000 | |
| iter = 49, accuracy (cur) = 0.620000 (all), 0.555556 (pos), 0.695652 (neg) | |
| iter = 49, accuracy (avg) = 0.259217 (all), 0.239436 (pos), 0.284573 (neg) | |
| data reader: epoch = 0, batch = 50 / 4040 | |
| iter = 50, cls_loss (cur) = 0.622120, cls_loss (avg) = 0.249012, lr = 0.010000 | |
| iter = 50, accuracy (cur) = 0.640000 (all), 0.590909 (pos), 0.678571 (neg) | |
| iter = 50, accuracy (avg) = 0.263025 (all), 0.242951 (pos), 0.288513 (neg) | |
| data reader: epoch = 0, batch = 51 / 4040 | |
| iter = 51, cls_loss (cur) = 0.583544, cls_loss (avg) = 0.252357, lr = 0.010000 | |
| iter = 51, accuracy (cur) = 0.700000 (all), 0.541667 (pos), 0.846154 (neg) | |
| iter = 51, accuracy (avg) = 0.267394 (all), 0.245938 (pos), 0.294090 (neg) | |
| data reader: epoch = 0, batch = 52 / 4040 | |
| iter = 52, cls_loss (cur) = 0.571088, cls_loss (avg) = 0.255545, lr = 0.010000 | |
| iter = 52, accuracy (cur) = 0.720000 (all), 0.666667 (pos), 0.782609 (neg) | |
| iter = 52, accuracy (avg) = 0.271920 (all), 0.250145 (pos), 0.298975 (neg) | |
| data reader: epoch = 0, batch = 53 / 4040 | |
| iter = 53, cls_loss (cur) = 0.553679, cls_loss (avg) = 0.258526, lr = 0.010000 | |
| iter = 53, accuracy (cur) = 0.680000 (all), 0.565217 (pos), 0.777778 (neg) | |
| iter = 53, accuracy (avg) = 0.276001 (all), 0.253296 (pos), 0.303763 (neg) | |
| data reader: epoch = 0, batch = 54 / 4040 | |
| iter = 54, cls_loss (cur) = 0.667883, cls_loss (avg) = 0.262620, lr = 0.010000 | |
| iter = 54, accuracy (cur) = 0.580000 (all), 0.619048 (pos), 0.551724 (neg) | |
| iter = 54, accuracy (avg) = 0.279041 (all), 0.256953 (pos), 0.306243 (neg) | |
| data reader: epoch = 0, batch = 55 / 4040 | |
| iter = 55, cls_loss (cur) = 0.535277, cls_loss (avg) = 0.265346, lr = 0.010000 | |
| iter = 55, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 55, accuracy (avg) = 0.284051 (all), 0.261692 (pos), 0.311513 (neg) | |
| data reader: epoch = 0, batch = 56 / 4040 | |
| iter = 56, cls_loss (cur) = 0.680614, cls_loss (avg) = 0.269499, lr = 0.010000 | |
| iter = 56, accuracy (cur) = 0.540000 (all), 0.391304 (pos), 0.666667 (neg) | |
| iter = 56, accuracy (avg) = 0.286610 (all), 0.262988 (pos), 0.315065 (neg) | |
| data reader: epoch = 0, batch = 57 / 4040 | |
| iter = 57, cls_loss (cur) = 0.560522, cls_loss (avg) = 0.272409, lr = 0.010000 | |
| iter = 57, accuracy (cur) = 0.720000 (all), 0.600000 (pos), 0.900000 (neg) | |
| iter = 57, accuracy (avg) = 0.290944 (all), 0.266358 (pos), 0.320914 (neg) | |
| data reader: epoch = 0, batch = 58 / 4040 | |
| iter = 58, cls_loss (cur) = 0.625674, cls_loss (avg) = 0.275942, lr = 0.010000 | |
| iter = 58, accuracy (cur) = 0.660000 (all), 0.538462 (pos), 0.791667 (neg) | |
| iter = 58, accuracy (avg) = 0.294635 (all), 0.269079 (pos), 0.325622 (neg) | |
| data reader: epoch = 0, batch = 59 / 4040 | |
| iter = 59, cls_loss (cur) = 0.566710, cls_loss (avg) = 0.278849, lr = 0.010000 | |
| iter = 59, accuracy (cur) = 0.700000 (all), 0.555556 (pos), 0.781250 (neg) | |
| iter = 59, accuracy (avg) = 0.298688 (all), 0.271944 (pos), 0.330178 (neg) | |
| data reader: epoch = 0, batch = 60 / 4040 | |
| iter = 60, cls_loss (cur) = 0.577999, cls_loss (avg) = 0.281841, lr = 0.010000 | |
| iter = 60, accuracy (cur) = 0.680000 (all), 0.586207 (pos), 0.809524 (neg) | |
| iter = 60, accuracy (avg) = 0.302501 (all), 0.275086 (pos), 0.334972 (neg) | |
| data reader: epoch = 0, batch = 61 / 4040 | |
| iter = 61, cls_loss (cur) = 0.607843, cls_loss (avg) = 0.285101, lr = 0.010000 | |
| iter = 61, accuracy (cur) = 0.660000 (all), 0.551724 (pos), 0.809524 (neg) | |
| iter = 61, accuracy (avg) = 0.306076 (all), 0.277853 (pos), 0.339717 (neg) | |
| data reader: epoch = 0, batch = 62 / 4040 | |
| iter = 62, cls_loss (cur) = 0.596767, cls_loss (avg) = 0.288218, lr = 0.010000 | |
| iter = 62, accuracy (cur) = 0.680000 (all), 0.608696 (pos), 0.740741 (neg) | |
| iter = 62, accuracy (avg) = 0.309816 (all), 0.281161 (pos), 0.343727 (neg) | |
| data reader: epoch = 0, batch = 63 / 4040 | |
| iter = 63, cls_loss (cur) = 0.526227, cls_loss (avg) = 0.290598, lr = 0.010000 | |
| iter = 63, accuracy (cur) = 0.800000 (all), 0.700000 (pos), 0.866667 (neg) | |
| iter = 63, accuracy (avg) = 0.314718 (all), 0.285350 (pos), 0.348957 (neg) | |
| data reader: epoch = 0, batch = 64 / 4040 | |
| iter = 64, cls_loss (cur) = 0.550827, cls_loss (avg) = 0.293200, lr = 0.010000 | |
| iter = 64, accuracy (cur) = 0.700000 (all), 0.727273 (pos), 0.678571 (neg) | |
| iter = 64, accuracy (avg) = 0.318570 (all), 0.289769 (pos), 0.352253 (neg) | |
| data reader: epoch = 0, batch = 65 / 4040 | |
| iter = 65, cls_loss (cur) = 0.552565, cls_loss (avg) = 0.295794, lr = 0.010000 | |
| iter = 65, accuracy (cur) = 0.740000 (all), 0.733333 (pos), 0.750000 (neg) | |
| iter = 65, accuracy (avg) = 0.322785 (all), 0.294204 (pos), 0.356230 (neg) | |
| data reader: epoch = 0, batch = 66 / 4040 | |
| iter = 66, cls_loss (cur) = 0.558617, cls_loss (avg) = 0.298422, lr = 0.010000 | |
| iter = 66, accuracy (cur) = 0.700000 (all), 0.653846 (pos), 0.750000 (neg) | |
| iter = 66, accuracy (avg) = 0.326557 (all), 0.297801 (pos), 0.360168 (neg) | |
| data reader: epoch = 0, batch = 67 / 4040 | |
| iter = 67, cls_loss (cur) = 0.551803, cls_loss (avg) = 0.300956, lr = 0.010000 | |
| iter = 67, accuracy (cur) = 0.700000 (all), 0.529412 (pos), 0.787879 (neg) | |
| iter = 67, accuracy (avg) = 0.330291 (all), 0.300117 (pos), 0.364445 (neg) | |
| data reader: epoch = 0, batch = 68 / 4040 | |
| iter = 68, cls_loss (cur) = 0.614145, cls_loss (avg) = 0.304088, lr = 0.010000 | |
| iter = 68, accuracy (cur) = 0.640000 (all), 0.434783 (pos), 0.814815 (neg) | |
| iter = 68, accuracy (avg) = 0.333388 (all), 0.301464 (pos), 0.368949 (neg) | |
| data reader: epoch = 0, batch = 69 / 4040 | |
| iter = 69, cls_loss (cur) = 0.595407, cls_loss (avg) = 0.307001, lr = 0.010000 | |
| iter = 69, accuracy (cur) = 0.620000 (all), 0.571429 (pos), 0.733333 (neg) | |
| iter = 69, accuracy (avg) = 0.336254 (all), 0.304163 (pos), 0.372593 (neg) | |
| data reader: epoch = 0, batch = 70 / 4040 | |
| iter = 70, cls_loss (cur) = 0.659171, cls_loss (avg) = 0.310523, lr = 0.010000 | |
| iter = 70, accuracy (cur) = 0.600000 (all), 0.434783 (pos), 0.740741 (neg) | |
| iter = 70, accuracy (avg) = 0.338892 (all), 0.305469 (pos), 0.376274 (neg) | |
| data reader: epoch = 0, batch = 71 / 4040 | |
| iter = 71, cls_loss (cur) = 0.621206, cls_loss (avg) = 0.313629, lr = 0.010000 | |
| iter = 71, accuracy (cur) = 0.640000 (all), 0.428571 (pos), 0.909091 (neg) | |
| iter = 71, accuracy (avg) = 0.341903 (all), 0.306700 (pos), 0.381602 (neg) | |
| data reader: epoch = 0, batch = 72 / 4040 | |
| iter = 72, cls_loss (cur) = 0.548109, cls_loss (avg) = 0.315974, lr = 0.010000 | |
| iter = 72, accuracy (cur) = 0.700000 (all), 0.590909 (pos), 0.785714 (neg) | |
| iter = 72, accuracy (avg) = 0.345484 (all), 0.309543 (pos), 0.385643 (neg) | |
| data reader: epoch = 0, batch = 73 / 4040 | |
| iter = 73, cls_loss (cur) = 0.667744, cls_loss (avg) = 0.319492, lr = 0.010000 | |
| iter = 73, accuracy (cur) = 0.560000 (all), 0.500000 (pos), 0.615385 (neg) | |
| iter = 73, accuracy (avg) = 0.347629 (all), 0.311447 (pos), 0.387941 (neg) | |
| data reader: epoch = 0, batch = 74 / 4040 | |
| iter = 74, cls_loss (cur) = 0.514700, cls_loss (avg) = 0.321444, lr = 0.010000 | |
| iter = 74, accuracy (cur) = 0.780000 (all), 0.727273 (pos), 0.821429 (neg) | |
| iter = 74, accuracy (avg) = 0.351953 (all), 0.315605 (pos), 0.392276 (neg) | |
| data reader: epoch = 0, batch = 75 / 4040 | |
| iter = 75, cls_loss (cur) = 0.601478, cls_loss (avg) = 0.324244, lr = 0.010000 | |
| iter = 75, accuracy (cur) = 0.680000 (all), 0.600000 (pos), 0.733333 (neg) | |
| iter = 75, accuracy (avg) = 0.355233 (all), 0.318449 (pos), 0.395686 (neg) | |
| data reader: epoch = 0, batch = 76 / 4040 | |
| iter = 76, cls_loss (cur) = 0.654221, cls_loss (avg) = 0.327544, lr = 0.010000 | |
| iter = 76, accuracy (cur) = 0.640000 (all), 0.480000 (pos), 0.800000 (neg) | |
| iter = 76, accuracy (avg) = 0.358081 (all), 0.320065 (pos), 0.399729 (neg) | |
| data reader: epoch = 0, batch = 77 / 4040 | |
| iter = 77, cls_loss (cur) = 0.594400, cls_loss (avg) = 0.330213, lr = 0.010000 | |
| iter = 77, accuracy (cur) = 0.680000 (all), 0.571429 (pos), 0.758621 (neg) | |
| iter = 77, accuracy (avg) = 0.361300 (all), 0.322578 (pos), 0.403318 (neg) | |
| data reader: epoch = 0, batch = 78 / 4040 | |
| iter = 78, cls_loss (cur) = 0.611462, cls_loss (avg) = 0.333025, lr = 0.010000 | |
| iter = 78, accuracy (cur) = 0.680000 (all), 0.642857 (pos), 0.727273 (neg) | |
| iter = 78, accuracy (avg) = 0.364487 (all), 0.325781 (pos), 0.406558 (neg) | |
| data reader: epoch = 0, batch = 79 / 4040 | |
| iter = 79, cls_loss (cur) = 0.641487, cls_loss (avg) = 0.336110, lr = 0.010000 | |
| iter = 79, accuracy (cur) = 0.620000 (all), 0.384615 (pos), 0.875000 (neg) | |
| iter = 79, accuracy (avg) = 0.367042 (all), 0.326370 (pos), 0.411242 (neg) | |
| data reader: epoch = 0, batch = 80 / 4040 | |
| iter = 80, cls_loss (cur) = 0.591736, cls_loss (avg) = 0.338666, lr = 0.010000 | |
| iter = 80, accuracy (cur) = 0.640000 (all), 0.500000 (pos), 0.769231 (neg) | |
| iter = 80, accuracy (avg) = 0.369772 (all), 0.328106 (pos), 0.414822 (neg) | |
| data reader: epoch = 0, batch = 81 / 4040 | |
| iter = 81, cls_loss (cur) = 0.603406, cls_loss (avg) = 0.341313, lr = 0.010000 | |
| iter = 81, accuracy (cur) = 0.620000 (all), 0.538462 (pos), 0.708333 (neg) | |
| iter = 81, accuracy (avg) = 0.372274 (all), 0.330209 (pos), 0.417757 (neg) | |
| data reader: epoch = 0, batch = 82 / 4040 | |
| iter = 82, cls_loss (cur) = 0.638032, cls_loss (avg) = 0.344281, lr = 0.010000 | |
| iter = 82, accuracy (cur) = 0.680000 (all), 0.560000 (pos), 0.800000 (neg) | |
| iter = 82, accuracy (avg) = 0.375351 (all), 0.332507 (pos), 0.421580 (neg) | |
| data reader: epoch = 0, batch = 83 / 4040 | |
| iter = 83, cls_loss (cur) = 0.524784, cls_loss (avg) = 0.346086, lr = 0.010000 | |
| iter = 83, accuracy (cur) = 0.780000 (all), 0.625000 (pos), 0.923077 (neg) | |
| iter = 83, accuracy (avg) = 0.379398 (all), 0.335432 (pos), 0.426595 (neg) | |
| data reader: epoch = 0, batch = 84 / 4040 | |
| iter = 84, cls_loss (cur) = 0.575073, cls_loss (avg) = 0.348375, lr = 0.010000 | |
| iter = 84, accuracy (cur) = 0.680000 (all), 0.615385 (pos), 0.750000 (neg) | |
| iter = 84, accuracy (avg) = 0.382404 (all), 0.338232 (pos), 0.429829 (neg) | |
| data reader: epoch = 0, batch = 85 / 4040 | |
| iter = 85, cls_loss (cur) = 0.485951, cls_loss (avg) = 0.349751, lr = 0.010000 | |
| iter = 85, accuracy (cur) = 0.760000 (all), 0.761905 (pos), 0.758621 (neg) | |
| iter = 85, accuracy (avg) = 0.386180 (all), 0.342469 (pos), 0.433117 (neg) | |
| data reader: epoch = 0, batch = 86 / 4040 | |
| iter = 86, cls_loss (cur) = 0.675718, cls_loss (avg) = 0.353011, lr = 0.010000 | |
| iter = 86, accuracy (cur) = 0.580000 (all), 0.409091 (pos), 0.714286 (neg) | |
| iter = 86, accuracy (avg) = 0.388118 (all), 0.343135 (pos), 0.435928 (neg) | |
| data reader: epoch = 0, batch = 87 / 4040 | |
| iter = 87, cls_loss (cur) = 0.576735, cls_loss (avg) = 0.355248, lr = 0.010000 | |
| iter = 87, accuracy (cur) = 0.700000 (all), 0.653846 (pos), 0.750000 (neg) | |
| iter = 87, accuracy (avg) = 0.391237 (all), 0.346242 (pos), 0.439069 (neg) | |
| data reader: epoch = 0, batch = 88 / 4040 | |
| iter = 88, cls_loss (cur) = 0.562228, cls_loss (avg) = 0.357318, lr = 0.010000 | |
| iter = 88, accuracy (cur) = 0.760000 (all), 0.615385 (pos), 0.916667 (neg) | |
| iter = 88, accuracy (avg) = 0.394925 (all), 0.348933 (pos), 0.443845 (neg) | |
| data reader: epoch = 0, batch = 89 / 4040 | |
| iter = 89, cls_loss (cur) = 0.583932, cls_loss (avg) = 0.359584, lr = 0.010000 | |
| iter = 89, accuracy (cur) = 0.700000 (all), 0.600000 (pos), 0.850000 (neg) | |
| iter = 89, accuracy (avg) = 0.397975 (all), 0.351444 (pos), 0.447907 (neg) | |
| data reader: epoch = 0, batch = 90 / 4040 | |
| iter = 90, cls_loss (cur) = 0.634015, cls_loss (avg) = 0.362328, lr = 0.010000 | |
| iter = 90, accuracy (cur) = 0.580000 (all), 0.409091 (pos), 0.714286 (neg) | |
| iter = 90, accuracy (avg) = 0.399796 (all), 0.352020 (pos), 0.450570 (neg) | |
| data reader: epoch = 0, batch = 91 / 4040 | |
| iter = 91, cls_loss (cur) = 0.578546, cls_loss (avg) = 0.364491, lr = 0.010000 | |
| iter = 91, accuracy (cur) = 0.680000 (all), 0.590909 (pos), 0.750000 (neg) | |
| iter = 91, accuracy (avg) = 0.402598 (all), 0.354409 (pos), 0.453565 (neg) | |
| data reader: epoch = 0, batch = 92 / 4040 | |
| iter = 92, cls_loss (cur) = 0.566981, cls_loss (avg) = 0.366515, lr = 0.010000 | |
| iter = 92, accuracy (cur) = 0.660000 (all), 0.642857 (pos), 0.681818 (neg) | |
| iter = 92, accuracy (avg) = 0.405172 (all), 0.357294 (pos), 0.455847 (neg) | |
| data reader: epoch = 0, batch = 93 / 4040 | |
| iter = 93, cls_loss (cur) = 0.621296, cls_loss (avg) = 0.369063, lr = 0.010000 | |
| iter = 93, accuracy (cur) = 0.620000 (all), 0.551724 (pos), 0.714286 (neg) | |
| iter = 93, accuracy (avg) = 0.407320 (all), 0.359238 (pos), 0.458432 (neg) | |
| data reader: epoch = 0, batch = 94 / 4040 | |
| iter = 94, cls_loss (cur) = 0.565867, cls_loss (avg) = 0.371031, lr = 0.010000 | |
| iter = 94, accuracy (cur) = 0.680000 (all), 0.578947 (pos), 0.741935 (neg) | |
| iter = 94, accuracy (avg) = 0.410047 (all), 0.361435 (pos), 0.461267 (neg) | |
| data reader: epoch = 0, batch = 95 / 4040 | |
| iter = 95, cls_loss (cur) = 0.572435, cls_loss (avg) = 0.373045, lr = 0.010000 | |
| iter = 95, accuracy (cur) = 0.660000 (all), 0.583333 (pos), 0.730769 (neg) | |
| iter = 95, accuracy (avg) = 0.412546 (all), 0.363654 (pos), 0.463962 (neg) | |
| data reader: epoch = 0, batch = 96 / 4040 | |
| iter = 96, cls_loss (cur) = 0.613580, cls_loss (avg) = 0.375451, lr = 0.010000 | |
| iter = 96, accuracy (cur) = 0.600000 (all), 0.545455 (pos), 0.642857 (neg) | |
| iter = 96, accuracy (avg) = 0.414421 (all), 0.365472 (pos), 0.465751 (neg) | |
| data reader: epoch = 0, batch = 97 / 4040 | |
| iter = 97, cls_loss (cur) = 0.670064, cls_loss (avg) = 0.378397, lr = 0.010000 | |
| iter = 97, accuracy (cur) = 0.620000 (all), 0.466667 (pos), 0.850000 (neg) | |
| iter = 97, accuracy (avg) = 0.416477 (all), 0.366484 (pos), 0.469593 (neg) | |
| data reader: epoch = 0, batch = 98 / 4040 | |
| iter = 98, cls_loss (cur) = 0.531617, cls_loss (avg) = 0.379929, lr = 0.010000 | |
| iter = 98, accuracy (cur) = 0.740000 (all), 0.625000 (pos), 0.846154 (neg) | |
| iter = 98, accuracy (avg) = 0.419712 (all), 0.369069 (pos), 0.473359 (neg) | |
| data reader: epoch = 0, batch = 99 / 4040 | |
| iter = 99, cls_loss (cur) = 0.572785, cls_loss (avg) = 0.381858, lr = 0.010000 | |
| iter = 99, accuracy (cur) = 0.720000 (all), 0.608696 (pos), 0.814815 (neg) | |
| iter = 99, accuracy (avg) = 0.422715 (all), 0.371466 (pos), 0.476773 (neg) | |
| data reader: epoch = 0, batch = 100 / 4040 | |
| iter = 100, cls_loss (cur) = 0.607573, cls_loss (avg) = 0.384115, lr = 0.010000 | |
| iter = 100, accuracy (cur) = 0.680000 (all), 0.566667 (pos), 0.850000 (neg) | |
| iter = 100, accuracy (avg) = 0.425288 (all), 0.373418 (pos), 0.480506 (neg) | |
| data reader: epoch = 0, batch = 101 / 4040 | |
| iter = 101, cls_loss (cur) = 0.525263, cls_loss (avg) = 0.385526, lr = 0.010000 | |
| iter = 101, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.857143 (neg) | |
| iter = 101, accuracy (avg) = 0.429035 (all), 0.376956 (pos), 0.484272 (neg) | |
| data reader: epoch = 0, batch = 102 / 4040 | |
| iter = 102, cls_loss (cur) = 0.564312, cls_loss (avg) = 0.387314, lr = 0.010000 | |
| iter = 102, accuracy (cur) = 0.740000 (all), 0.695652 (pos), 0.777778 (neg) | |
| iter = 102, accuracy (avg) = 0.432144 (all), 0.380143 (pos), 0.487207 (neg) | |
| data reader: epoch = 0, batch = 103 / 4040 | |
| iter = 103, cls_loss (cur) = 0.677946, cls_loss (avg) = 0.390220, lr = 0.010000 | |
| iter = 103, accuracy (cur) = 0.600000 (all), 0.433333 (pos), 0.850000 (neg) | |
| iter = 103, accuracy (avg) = 0.433823 (all), 0.380675 (pos), 0.490835 (neg) | |
| data reader: epoch = 0, batch = 104 / 4040 | |
| iter = 104, cls_loss (cur) = 0.591378, cls_loss (avg) = 0.392232, lr = 0.010000 | |
| iter = 104, accuracy (cur) = 0.660000 (all), 0.576923 (pos), 0.750000 (neg) | |
| iter = 104, accuracy (avg) = 0.436085 (all), 0.382637 (pos), 0.493427 (neg) | |
| data reader: epoch = 0, batch = 105 / 4040 | |
| iter = 105, cls_loss (cur) = 0.580072, cls_loss (avg) = 0.394110, lr = 0.010000 | |
| iter = 105, accuracy (cur) = 0.680000 (all), 0.560000 (pos), 0.800000 (neg) | |
| iter = 105, accuracy (avg) = 0.438524 (all), 0.384411 (pos), 0.496492 (neg) | |
| data reader: epoch = 0, batch = 106 / 4040 | |
| iter = 106, cls_loss (cur) = 0.583696, cls_loss (avg) = 0.396006, lr = 0.010000 | |
| iter = 106, accuracy (cur) = 0.620000 (all), 0.640000 (pos), 0.600000 (neg) | |
| iter = 106, accuracy (avg) = 0.440339 (all), 0.386967 (pos), 0.497527 (neg) | |
| data reader: epoch = 0, batch = 107 / 4040 | |
| iter = 107, cls_loss (cur) = 0.573849, cls_loss (avg) = 0.397785, lr = 0.010000 | |
| iter = 107, accuracy (cur) = 0.720000 (all), 0.700000 (pos), 0.733333 (neg) | |
| iter = 107, accuracy (avg) = 0.443135 (all), 0.390097 (pos), 0.499885 (neg) | |
| data reader: epoch = 0, batch = 108 / 4040 | |
| iter = 108, cls_loss (cur) = 0.631917, cls_loss (avg) = 0.400126, lr = 0.010000 | |
| iter = 108, accuracy (cur) = 0.600000 (all), 0.538462 (pos), 0.666667 (neg) | |
| iter = 108, accuracy (avg) = 0.444704 (all), 0.391581 (pos), 0.501553 (neg) | |
| data reader: epoch = 0, batch = 109 / 4040 | |
| iter = 109, cls_loss (cur) = 0.642044, cls_loss (avg) = 0.402545, lr = 0.010000 | |
| iter = 109, accuracy (cur) = 0.660000 (all), 0.600000 (pos), 0.750000 (neg) | |
| iter = 109, accuracy (avg) = 0.446857 (all), 0.393665 (pos), 0.504038 (neg) | |
| data reader: epoch = 0, batch = 110 / 4040 | |
| iter = 110, cls_loss (cur) = 0.568012, cls_loss (avg) = 0.404200, lr = 0.010000 | |
| iter = 110, accuracy (cur) = 0.660000 (all), 0.590909 (pos), 0.714286 (neg) | |
| iter = 110, accuracy (avg) = 0.448988 (all), 0.395638 (pos), 0.506140 (neg) | |
| data reader: epoch = 0, batch = 111 / 4040 | |
| iter = 111, cls_loss (cur) = 0.532455, cls_loss (avg) = 0.405482, lr = 0.010000 | |
| iter = 111, accuracy (cur) = 0.760000 (all), 0.636364 (pos), 0.857143 (neg) | |
| iter = 111, accuracy (avg) = 0.452098 (all), 0.398045 (pos), 0.509650 (neg) | |
| data reader: epoch = 0, batch = 112 / 4040 | |
| iter = 112, cls_loss (cur) = 0.551050, cls_loss (avg) = 0.406938, lr = 0.010000 | |
| iter = 112, accuracy (cur) = 0.660000 (all), 0.590909 (pos), 0.714286 (neg) | |
| iter = 112, accuracy (avg) = 0.454177 (all), 0.399973 (pos), 0.511697 (neg) | |
| data reader: epoch = 0, batch = 113 / 4040 | |
| iter = 113, cls_loss (cur) = 0.568864, cls_loss (avg) = 0.408557, lr = 0.010000 | |
| iter = 113, accuracy (cur) = 0.700000 (all), 0.571429 (pos), 0.863636 (neg) | |
| iter = 113, accuracy (avg) = 0.456636 (all), 0.401688 (pos), 0.515216 (neg) | |
| data reader: epoch = 0, batch = 114 / 4040 | |
| iter = 114, cls_loss (cur) = 0.552247, cls_loss (avg) = 0.409994, lr = 0.010000 | |
| iter = 114, accuracy (cur) = 0.700000 (all), 0.620690 (pos), 0.809524 (neg) | |
| iter = 114, accuracy (avg) = 0.459069 (all), 0.403878 (pos), 0.518159 (neg) | |
| data reader: epoch = 0, batch = 115 / 4040 | |
| iter = 115, cls_loss (cur) = 0.625005, cls_loss (avg) = 0.412144, lr = 0.010000 | |
| iter = 115, accuracy (cur) = 0.640000 (all), 0.611111 (pos), 0.656250 (neg) | |
| iter = 115, accuracy (avg) = 0.460879 (all), 0.405950 (pos), 0.519540 (neg) | |
| data reader: epoch = 0, batch = 116 / 4040 | |
| iter = 116, cls_loss (cur) = 0.487931, cls_loss (avg) = 0.412902, lr = 0.010000 | |
| iter = 116, accuracy (cur) = 0.760000 (all), 0.807692 (pos), 0.708333 (neg) | |
| iter = 116, accuracy (avg) = 0.463870 (all), 0.409968 (pos), 0.521428 (neg) | |
| data reader: epoch = 0, batch = 117 / 4040 | |
| iter = 117, cls_loss (cur) = 0.559873, cls_loss (avg) = 0.414372, lr = 0.010000 | |
| iter = 117, accuracy (cur) = 0.680000 (all), 0.500000 (pos), 0.875000 (neg) | |
| iter = 117, accuracy (avg) = 0.466031 (all), 0.410868 (pos), 0.524964 (neg) | |
| data reader: epoch = 0, batch = 118 / 4040 | |
| iter = 118, cls_loss (cur) = 0.591835, cls_loss (avg) = 0.416147, lr = 0.010000 | |
| iter = 118, accuracy (cur) = 0.720000 (all), 0.538462 (pos), 0.916667 (neg) | |
| iter = 118, accuracy (avg) = 0.468571 (all), 0.412144 (pos), 0.528881 (neg) | |
| data reader: epoch = 0, batch = 119 / 4040 | |
| iter = 119, cls_loss (cur) = 0.599072, cls_loss (avg) = 0.417976, lr = 0.010000 | |
| iter = 119, accuracy (cur) = 0.640000 (all), 0.633333 (pos), 0.650000 (neg) | |
| iter = 119, accuracy (avg) = 0.470285 (all), 0.414356 (pos), 0.530092 (neg) | |
| data reader: epoch = 0, batch = 120 / 4040 | |
| iter = 120, cls_loss (cur) = 0.607175, cls_loss (avg) = 0.419868, lr = 0.010000 | |
| iter = 120, accuracy (cur) = 0.600000 (all), 0.551724 (pos), 0.666667 (neg) | |
| iter = 120, accuracy (avg) = 0.471582 (all), 0.415730 (pos), 0.531458 (neg) | |
| data reader: epoch = 0, batch = 121 / 4040 | |
| iter = 121, cls_loss (cur) = 0.522447, cls_loss (avg) = 0.420894, lr = 0.010000 | |
| iter = 121, accuracy (cur) = 0.720000 (all), 0.760000 (pos), 0.680000 (neg) | |
| iter = 121, accuracy (avg) = 0.474066 (all), 0.419172 (pos), 0.532943 (neg) | |
| data reader: epoch = 0, batch = 122 / 4040 | |
| iter = 122, cls_loss (cur) = 0.619214, cls_loss (avg) = 0.422877, lr = 0.010000 | |
| iter = 122, accuracy (cur) = 0.640000 (all), 0.409091 (pos), 0.821429 (neg) | |
| iter = 122, accuracy (avg) = 0.475726 (all), 0.419072 (pos), 0.535828 (neg) | |
| data reader: epoch = 0, batch = 123 / 4040 | |
| iter = 123, cls_loss (cur) = 0.548216, cls_loss (avg) = 0.424130, lr = 0.010000 | |
| iter = 123, accuracy (cur) = 0.720000 (all), 0.652174 (pos), 0.777778 (neg) | |
| iter = 123, accuracy (avg) = 0.478168 (all), 0.421403 (pos), 0.538247 (neg) | |
| data reader: epoch = 0, batch = 124 / 4040 | |
| iter = 124, cls_loss (cur) = 0.621100, cls_loss (avg) = 0.426100, lr = 0.010000 | |
| iter = 124, accuracy (cur) = 0.600000 (all), 0.419355 (pos), 0.894737 (neg) | |
| iter = 124, accuracy (avg) = 0.479387 (all), 0.421382 (pos), 0.541812 (neg) | |
| data reader: epoch = 0, batch = 125 / 4040 | |
| iter = 125, cls_loss (cur) = 0.490611, cls_loss (avg) = 0.426745, lr = 0.010000 | |
| iter = 125, accuracy (cur) = 0.800000 (all), 0.863636 (pos), 0.750000 (neg) | |
| iter = 125, accuracy (avg) = 0.482593 (all), 0.425805 (pos), 0.543894 (neg) | |
| data reader: epoch = 0, batch = 126 / 4040 | |
| iter = 126, cls_loss (cur) = 0.612028, cls_loss (avg) = 0.428598, lr = 0.010000 | |
| iter = 126, accuracy (cur) = 0.660000 (all), 0.545455 (pos), 0.750000 (neg) | |
| iter = 126, accuracy (avg) = 0.484367 (all), 0.427001 (pos), 0.545955 (neg) | |
| data reader: epoch = 0, batch = 127 / 4040 | |
| iter = 127, cls_loss (cur) = 0.548970, cls_loss (avg) = 0.429802, lr = 0.010000 | |
| iter = 127, accuracy (cur) = 0.680000 (all), 0.652174 (pos), 0.703704 (neg) | |
| iter = 127, accuracy (avg) = 0.486323 (all), 0.429253 (pos), 0.547533 (neg) | |
| data reader: epoch = 0, batch = 128 / 4040 | |
| iter = 128, cls_loss (cur) = 0.530710, cls_loss (avg) = 0.430811, lr = 0.010000 | |
| iter = 128, accuracy (cur) = 0.740000 (all), 0.541667 (pos), 0.923077 (neg) | |
| iter = 128, accuracy (avg) = 0.488860 (all), 0.430377 (pos), 0.551288 (neg) | |
| data reader: epoch = 0, batch = 129 / 4040 | |
| iter = 129, cls_loss (cur) = 0.567502, cls_loss (avg) = 0.432178, lr = 0.010000 | |
| iter = 129, accuracy (cur) = 0.620000 (all), 0.518519 (pos), 0.739130 (neg) | |
| iter = 129, accuracy (avg) = 0.490171 (all), 0.431258 (pos), 0.553167 (neg) | |
| data reader: epoch = 0, batch = 130 / 4040 | |
| iter = 130, cls_loss (cur) = 0.592615, cls_loss (avg) = 0.433782, lr = 0.010000 | |
| iter = 130, accuracy (cur) = 0.660000 (all), 0.678571 (pos), 0.636364 (neg) | |
| iter = 130, accuracy (avg) = 0.491870 (all), 0.433732 (pos), 0.553999 (neg) | |
| data reader: epoch = 0, batch = 131 / 4040 | |
| iter = 131, cls_loss (cur) = 0.579109, cls_loss (avg) = 0.435235, lr = 0.010000 | |
| iter = 131, accuracy (cur) = 0.700000 (all), 0.681818 (pos), 0.714286 (neg) | |
| iter = 131, accuracy (avg) = 0.493951 (all), 0.436212 (pos), 0.555601 (neg) | |
| data reader: epoch = 0, batch = 132 / 4040 | |
| iter = 132, cls_loss (cur) = 0.548521, cls_loss (avg) = 0.436368, lr = 0.010000 | |
| iter = 132, accuracy (cur) = 0.740000 (all), 0.640000 (pos), 0.840000 (neg) | |
| iter = 132, accuracy (avg) = 0.496412 (all), 0.438250 (pos), 0.558445 (neg) | |
| data reader: epoch = 0, batch = 133 / 4040 | |
| iter = 133, cls_loss (cur) = 0.430996, cls_loss (avg) = 0.436314, lr = 0.010000 | |
| iter = 133, accuracy (cur) = 0.840000 (all), 0.724138 (pos), 1.000000 (neg) | |
| iter = 133, accuracy (avg) = 0.499847 (all), 0.441109 (pos), 0.562861 (neg) | |
| data reader: epoch = 0, batch = 134 / 4040 | |
| iter = 134, cls_loss (cur) = 0.669061, cls_loss (avg) = 0.438642, lr = 0.010000 | |
| iter = 134, accuracy (cur) = 0.560000 (all), 0.464286 (pos), 0.681818 (neg) | |
| iter = 134, accuracy (avg) = 0.500449 (all), 0.441341 (pos), 0.564051 (neg) | |
| data reader: epoch = 0, batch = 135 / 4040 | |
| iter = 135, cls_loss (cur) = 0.642281, cls_loss (avg) = 0.440678, lr = 0.010000 | |
| iter = 135, accuracy (cur) = 0.640000 (all), 0.566667 (pos), 0.750000 (neg) | |
| iter = 135, accuracy (avg) = 0.501844 (all), 0.442594 (pos), 0.565910 (neg) | |
| data reader: epoch = 0, batch = 136 / 4040 | |
| iter = 136, cls_loss (cur) = 0.579857, cls_loss (avg) = 0.442070, lr = 0.010000 | |
| iter = 136, accuracy (cur) = 0.660000 (all), 0.518519 (pos), 0.826087 (neg) | |
| iter = 136, accuracy (avg) = 0.503426 (all), 0.443353 (pos), 0.568512 (neg) | |
| data reader: epoch = 0, batch = 137 / 4040 | |
| iter = 137, cls_loss (cur) = 0.619147, cls_loss (avg) = 0.443841, lr = 0.010000 | |
| iter = 137, accuracy (cur) = 0.660000 (all), 0.518519 (pos), 0.826087 (neg) | |
| iter = 137, accuracy (avg) = 0.504992 (all), 0.444105 (pos), 0.571088 (neg) | |
| data reader: epoch = 0, batch = 138 / 4040 | |
| iter = 138, cls_loss (cur) = 0.652408, cls_loss (avg) = 0.445926, lr = 0.010000 | |
| iter = 138, accuracy (cur) = 0.580000 (all), 0.458333 (pos), 0.692308 (neg) | |
| iter = 138, accuracy (avg) = 0.505742 (all), 0.444247 (pos), 0.572300 (neg) | |
| data reader: epoch = 0, batch = 139 / 4040 | |
| iter = 139, cls_loss (cur) = 0.619313, cls_loss (avg) = 0.447660, lr = 0.010000 | |
| iter = 139, accuracy (cur) = 0.680000 (all), 0.772727 (pos), 0.607143 (neg) | |
| iter = 139, accuracy (avg) = 0.507484 (all), 0.447532 (pos), 0.572648 (neg) | |
| data reader: epoch = 0, batch = 140 / 4040 | |
| iter = 140, cls_loss (cur) = 0.616753, cls_loss (avg) = 0.449351, lr = 0.010000 | |
| iter = 140, accuracy (cur) = 0.680000 (all), 0.607143 (pos), 0.772727 (neg) | |
| iter = 140, accuracy (avg) = 0.509210 (all), 0.449128 (pos), 0.574649 (neg) | |
| data reader: epoch = 0, batch = 141 / 4040 | |
| iter = 141, cls_loss (cur) = 0.671166, cls_loss (avg) = 0.451569, lr = 0.010000 | |
| iter = 141, accuracy (cur) = 0.540000 (all), 0.590909 (pos), 0.500000 (neg) | |
| iter = 141, accuracy (avg) = 0.509517 (all), 0.450546 (pos), 0.573902 (neg) | |
| data reader: epoch = 0, batch = 142 / 4040 | |
| iter = 142, cls_loss (cur) = 0.594513, cls_loss (avg) = 0.452999, lr = 0.010000 | |
| iter = 142, accuracy (cur) = 0.580000 (all), 0.416667 (pos), 0.730769 (neg) | |
| iter = 142, accuracy (avg) = 0.510222 (all), 0.450207 (pos), 0.575471 (neg) | |
| data reader: epoch = 0, batch = 143 / 4040 | |
| iter = 143, cls_loss (cur) = 0.545946, cls_loss (avg) = 0.453928, lr = 0.010000 | |
| iter = 143, accuracy (cur) = 0.700000 (all), 0.680000 (pos), 0.720000 (neg) | |
| iter = 143, accuracy (avg) = 0.512120 (all), 0.452505 (pos), 0.576916 (neg) | |
| data reader: epoch = 0, batch = 144 / 4040 | |
| iter = 144, cls_loss (cur) = 0.621024, cls_loss (avg) = 0.455599, lr = 0.010000 | |
| iter = 144, accuracy (cur) = 0.680000 (all), 0.600000 (pos), 0.760000 (neg) | |
| iter = 144, accuracy (avg) = 0.513799 (all), 0.453980 (pos), 0.578747 (neg) | |
| data reader: epoch = 0, batch = 145 / 4040 | |
| iter = 145, cls_loss (cur) = 0.527580, cls_loss (avg) = 0.456319, lr = 0.010000 | |
| iter = 145, accuracy (cur) = 0.780000 (all), 0.692308 (pos), 0.875000 (neg) | |
| iter = 145, accuracy (avg) = 0.516461 (all), 0.456363 (pos), 0.581710 (neg) | |
| data reader: epoch = 0, batch = 146 / 4040 | |
| iter = 146, cls_loss (cur) = 0.576286, cls_loss (avg) = 0.457519, lr = 0.010000 | |
| iter = 146, accuracy (cur) = 0.740000 (all), 0.560000 (pos), 0.920000 (neg) | |
| iter = 146, accuracy (avg) = 0.518696 (all), 0.457400 (pos), 0.585093 (neg) | |
| data reader: epoch = 0, batch = 147 / 4040 | |
| iter = 147, cls_loss (cur) = 0.529656, cls_loss (avg) = 0.458240, lr = 0.010000 | |
| iter = 147, accuracy (cur) = 0.720000 (all), 0.678571 (pos), 0.772727 (neg) | |
| iter = 147, accuracy (avg) = 0.520709 (all), 0.459611 (pos), 0.586969 (neg) | |
| data reader: epoch = 0, batch = 148 / 4040 | |
| iter = 148, cls_loss (cur) = 0.556896, cls_loss (avg) = 0.459227, lr = 0.010000 | |
| iter = 148, accuracy (cur) = 0.700000 (all), 0.629630 (pos), 0.782609 (neg) | |
| iter = 148, accuracy (avg) = 0.522502 (all), 0.461312 (pos), 0.588925 (neg) | |
| data reader: epoch = 0, batch = 149 / 4040 | |
| iter = 149, cls_loss (cur) = 0.594844, cls_loss (avg) = 0.460583, lr = 0.010000 | |
| iter = 149, accuracy (cur) = 0.700000 (all), 0.608696 (pos), 0.777778 (neg) | |
| iter = 149, accuracy (avg) = 0.524277 (all), 0.462786 (pos), 0.590814 (neg) | |
| data reader: epoch = 0, batch = 150 / 4040 | |
| iter = 150, cls_loss (cur) = 0.551955, cls_loss (avg) = 0.461497, lr = 0.010000 | |
| iter = 150, accuracy (cur) = 0.740000 (all), 0.714286 (pos), 0.772727 (neg) | |
| iter = 150, accuracy (avg) = 0.526434 (all), 0.465301 (pos), 0.592633 (neg) | |
| data reader: epoch = 0, batch = 151 / 4040 | |
| iter = 151, cls_loss (cur) = 0.577606, cls_loss (avg) = 0.462658, lr = 0.010000 | |
| iter = 151, accuracy (cur) = 0.720000 (all), 0.791667 (pos), 0.653846 (neg) | |
| iter = 151, accuracy (avg) = 0.528370 (all), 0.468564 (pos), 0.593245 (neg) | |
| data reader: epoch = 0, batch = 152 / 4040 | |
| iter = 152, cls_loss (cur) = 0.547068, cls_loss (avg) = 0.463502, lr = 0.010000 | |
| iter = 152, accuracy (cur) = 0.720000 (all), 0.629630 (pos), 0.826087 (neg) | |
| iter = 152, accuracy (avg) = 0.530286 (all), 0.470175 (pos), 0.595574 (neg) | |
| data reader: epoch = 0, batch = 153 / 4040 | |
| iter = 153, cls_loss (cur) = 0.601542, cls_loss (avg) = 0.464882, lr = 0.010000 | |
| iter = 153, accuracy (cur) = 0.680000 (all), 0.625000 (pos), 0.730769 (neg) | |
| iter = 153, accuracy (avg) = 0.531784 (all), 0.471723 (pos), 0.596926 (neg) | |
| data reader: epoch = 0, batch = 154 / 4040 | |
| iter = 154, cls_loss (cur) = 0.597195, cls_loss (avg) = 0.466205, lr = 0.010000 | |
| iter = 154, accuracy (cur) = 0.660000 (all), 0.409091 (pos), 0.857143 (neg) | |
| iter = 154, accuracy (avg) = 0.533066 (all), 0.471097 (pos), 0.599528 (neg) | |
| data reader: epoch = 0, batch = 155 / 4040 | |
| iter = 155, cls_loss (cur) = 0.496409, cls_loss (avg) = 0.466507, lr = 0.010000 | |
| iter = 155, accuracy (cur) = 0.760000 (all), 0.629630 (pos), 0.913043 (neg) | |
| iter = 155, accuracy (avg) = 0.535335 (all), 0.472682 (pos), 0.602663 (neg) | |
| data reader: epoch = 0, batch = 156 / 4040 | |
| iter = 156, cls_loss (cur) = 0.620430, cls_loss (avg) = 0.468047, lr = 0.010000 | |
| iter = 156, accuracy (cur) = 0.640000 (all), 0.562500 (pos), 0.777778 (neg) | |
| iter = 156, accuracy (avg) = 0.536382 (all), 0.473580 (pos), 0.604414 (neg) | |
| data reader: epoch = 0, batch = 157 / 4040 | |
| iter = 157, cls_loss (cur) = 0.537379, cls_loss (avg) = 0.468740, lr = 0.010000 | |
| iter = 157, accuracy (cur) = 0.720000 (all), 0.666667 (pos), 0.769231 (neg) | |
| iter = 157, accuracy (avg) = 0.538218 (all), 0.475511 (pos), 0.606062 (neg) | |
| data reader: epoch = 0, batch = 158 / 4040 | |
| iter = 158, cls_loss (cur) = 0.593433, cls_loss (avg) = 0.469987, lr = 0.010000 | |
| iter = 158, accuracy (cur) = 0.700000 (all), 0.666667 (pos), 0.739130 (neg) | |
| iter = 158, accuracy (avg) = 0.539836 (all), 0.477423 (pos), 0.607393 (neg) | |
| data reader: epoch = 0, batch = 159 / 4040 | |
| iter = 159, cls_loss (cur) = 0.549745, cls_loss (avg) = 0.470784, lr = 0.010000 | |
| iter = 159, accuracy (cur) = 0.720000 (all), 0.681818 (pos), 0.750000 (neg) | |
| iter = 159, accuracy (avg) = 0.541637 (all), 0.479467 (pos), 0.608819 (neg) | |
| data reader: epoch = 0, batch = 160 / 4040 | |
| iter = 160, cls_loss (cur) = 0.593492, cls_loss (avg) = 0.472011, lr = 0.010000 | |
| iter = 160, accuracy (cur) = 0.620000 (all), 0.642857 (pos), 0.590909 (neg) | |
| iter = 160, accuracy (avg) = 0.542421 (all), 0.481101 (pos), 0.608640 (neg) | |
| data reader: epoch = 0, batch = 161 / 4040 | |
| iter = 161, cls_loss (cur) = 0.582785, cls_loss (avg) = 0.473119, lr = 0.010000 | |
| iter = 161, accuracy (cur) = 0.660000 (all), 0.642857 (pos), 0.681818 (neg) | |
| iter = 161, accuracy (avg) = 0.543597 (all), 0.482718 (pos), 0.609372 (neg) | |
| data reader: epoch = 0, batch = 162 / 4040 | |
| iter = 162, cls_loss (cur) = 0.489141, cls_loss (avg) = 0.473279, lr = 0.010000 | |
| iter = 162, accuracy (cur) = 0.700000 (all), 0.565217 (pos), 0.814815 (neg) | |
| iter = 162, accuracy (avg) = 0.545161 (all), 0.483543 (pos), 0.611426 (neg) | |
| data reader: epoch = 0, batch = 163 / 4040 | |
| iter = 163, cls_loss (cur) = 0.487994, cls_loss (avg) = 0.473427, lr = 0.010000 | |
| iter = 163, accuracy (cur) = 0.780000 (all), 0.700000 (pos), 0.900000 (neg) | |
| iter = 163, accuracy (avg) = 0.547509 (all), 0.485708 (pos), 0.614312 (neg) | |
| data reader: epoch = 0, batch = 164 / 4040 | |
| iter = 164, cls_loss (cur) = 0.591462, cls_loss (avg) = 0.474607, lr = 0.010000 | |
| iter = 164, accuracy (cur) = 0.660000 (all), 0.538462 (pos), 0.791667 (neg) | |
| iter = 164, accuracy (avg) = 0.548634 (all), 0.486235 (pos), 0.616085 (neg) | |
| data reader: epoch = 0, batch = 165 / 4040 | |
| iter = 165, cls_loss (cur) = 0.604886, cls_loss (avg) = 0.475910, lr = 0.010000 | |
| iter = 165, accuracy (cur) = 0.680000 (all), 0.652174 (pos), 0.703704 (neg) | |
| iter = 165, accuracy (avg) = 0.549948 (all), 0.487895 (pos), 0.616962 (neg) | |
| data reader: epoch = 0, batch = 166 / 4040 | |
| iter = 166, cls_loss (cur) = 0.579452, cls_loss (avg) = 0.476945, lr = 0.010000 | |
| iter = 166, accuracy (cur) = 0.660000 (all), 0.629630 (pos), 0.695652 (neg) | |
| iter = 166, accuracy (avg) = 0.551048 (all), 0.489312 (pos), 0.617748 (neg) | |
| data reader: epoch = 0, batch = 167 / 4040 | |
| iter = 167, cls_loss (cur) = 0.534826, cls_loss (avg) = 0.477524, lr = 0.010000 | |
| iter = 167, accuracy (cur) = 0.700000 (all), 0.689655 (pos), 0.714286 (neg) | |
| iter = 167, accuracy (avg) = 0.552538 (all), 0.491315 (pos), 0.618714 (neg) | |
| data reader: epoch = 0, batch = 168 / 4040 | |
| iter = 168, cls_loss (cur) = 0.554114, cls_loss (avg) = 0.478290, lr = 0.010000 | |
| iter = 168, accuracy (cur) = 0.660000 (all), 0.520000 (pos), 0.800000 (neg) | |
| iter = 168, accuracy (avg) = 0.553612 (all), 0.491602 (pos), 0.620527 (neg) | |
| data reader: epoch = 0, batch = 169 / 4040 | |
| iter = 169, cls_loss (cur) = 0.613027, cls_loss (avg) = 0.479637, lr = 0.010000 | |
| iter = 169, accuracy (cur) = 0.640000 (all), 0.600000 (pos), 0.680000 (neg) | |
| iter = 169, accuracy (avg) = 0.554476 (all), 0.492686 (pos), 0.621121 (neg) | |
| data reader: epoch = 0, batch = 170 / 4040 | |
| iter = 170, cls_loss (cur) = 0.493743, cls_loss (avg) = 0.479778, lr = 0.010000 | |
| iter = 170, accuracy (cur) = 0.780000 (all), 0.769231 (pos), 0.791667 (neg) | |
| iter = 170, accuracy (avg) = 0.556731 (all), 0.495452 (pos), 0.622827 (neg) | |
| data reader: epoch = 0, batch = 171 / 4040 | |
| iter = 171, cls_loss (cur) = 0.451835, cls_loss (avg) = 0.479499, lr = 0.010000 | |
| iter = 171, accuracy (cur) = 0.780000 (all), 0.833333 (pos), 0.730769 (neg) | |
| iter = 171, accuracy (avg) = 0.558964 (all), 0.498830 (pos), 0.623906 (neg) | |
| data reader: epoch = 0, batch = 172 / 4040 | |
| iter = 172, cls_loss (cur) = 0.553432, cls_loss (avg) = 0.480238, lr = 0.010000 | |
| iter = 172, accuracy (cur) = 0.700000 (all), 0.695652 (pos), 0.703704 (neg) | |
| iter = 172, accuracy (avg) = 0.560375 (all), 0.500799 (pos), 0.624704 (neg) | |
| data reader: epoch = 0, batch = 173 / 4040 | |
| iter = 173, cls_loss (cur) = 0.521558, cls_loss (avg) = 0.480651, lr = 0.010000 | |
| iter = 173, accuracy (cur) = 0.760000 (all), 0.600000 (pos), 0.866667 (neg) | |
| iter = 173, accuracy (avg) = 0.562371 (all), 0.501791 (pos), 0.627124 (neg) | |
| data reader: epoch = 0, batch = 174 / 4040 | |
| iter = 174, cls_loss (cur) = 0.609317, cls_loss (avg) = 0.481938, lr = 0.010000 | |
| iter = 174, accuracy (cur) = 0.620000 (all), 0.357143 (pos), 0.954545 (neg) | |
| iter = 174, accuracy (avg) = 0.562947 (all), 0.500344 (pos), 0.630398 (neg) | |
| data reader: epoch = 0, batch = 175 / 4040 | |
| iter = 175, cls_loss (cur) = 0.622071, cls_loss (avg) = 0.483339, lr = 0.010000 | |
| iter = 175, accuracy (cur) = 0.680000 (all), 0.608696 (pos), 0.740741 (neg) | |
| iter = 175, accuracy (avg) = 0.564118 (all), 0.501428 (pos), 0.631502 (neg) | |
| data reader: epoch = 0, batch = 176 / 4040 | |
| iter = 176, cls_loss (cur) = 0.611543, cls_loss (avg) = 0.484621, lr = 0.010000 | |
| iter = 176, accuracy (cur) = 0.620000 (all), 0.363636 (pos), 0.821429 (neg) | |
| iter = 176, accuracy (avg) = 0.564676 (all), 0.500050 (pos), 0.633401 (neg) | |
| data reader: epoch = 0, batch = 177 / 4040 | |
| iter = 177, cls_loss (cur) = 0.551619, cls_loss (avg) = 0.485291, lr = 0.010000 | |
| iter = 177, accuracy (cur) = 0.740000 (all), 0.478261 (pos), 0.962963 (neg) | |
| iter = 177, accuracy (avg) = 0.566430 (all), 0.499832 (pos), 0.636696 (neg) | |
| data reader: epoch = 0, batch = 178 / 4040 | |
| iter = 178, cls_loss (cur) = 0.526803, cls_loss (avg) = 0.485706, lr = 0.010000 | |
| iter = 178, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.807692 (neg) | |
| iter = 178, accuracy (avg) = 0.568165 (all), 0.501500 (pos), 0.638406 (neg) | |
| data reader: epoch = 0, batch = 179 / 4040 | |
| iter = 179, cls_loss (cur) = 0.547940, cls_loss (avg) = 0.486329, lr = 0.010000 | |
| iter = 179, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.826087 (neg) | |
| iter = 179, accuracy (avg) = 0.569884 (all), 0.503152 (pos), 0.640283 (neg) | |
| data reader: epoch = 0, batch = 180 / 4040 | |
| iter = 180, cls_loss (cur) = 0.592582, cls_loss (avg) = 0.487391, lr = 0.010000 | |
| iter = 180, accuracy (cur) = 0.680000 (all), 0.500000 (pos), 0.875000 (neg) | |
| iter = 180, accuracy (avg) = 0.570985 (all), 0.503120 (pos), 0.642630 (neg) | |
| data reader: epoch = 0, batch = 181 / 4040 | |
| iter = 181, cls_loss (cur) = 0.619316, cls_loss (avg) = 0.488711, lr = 0.010000 | |
| iter = 181, accuracy (cur) = 0.640000 (all), 0.636364 (pos), 0.642857 (neg) | |
| iter = 181, accuracy (avg) = 0.571675 (all), 0.504453 (pos), 0.642633 (neg) | |
| data reader: epoch = 0, batch = 182 / 4040 | |
| iter = 182, cls_loss (cur) = 0.680415, cls_loss (avg) = 0.490628, lr = 0.010000 | |
| iter = 182, accuracy (cur) = 0.520000 (all), 0.384615 (pos), 0.666667 (neg) | |
| iter = 182, accuracy (avg) = 0.571158 (all), 0.503254 (pos), 0.642873 (neg) | |
| data reader: epoch = 0, batch = 183 / 4040 | |
| iter = 183, cls_loss (cur) = 0.582454, cls_loss (avg) = 0.491546, lr = 0.010000 | |
| iter = 183, accuracy (cur) = 0.660000 (all), 0.541667 (pos), 0.769231 (neg) | |
| iter = 183, accuracy (avg) = 0.572047 (all), 0.503639 (pos), 0.644137 (neg) | |
| data reader: epoch = 0, batch = 184 / 4040 | |
| iter = 184, cls_loss (cur) = 0.556972, cls_loss (avg) = 0.492200, lr = 0.010000 | |
| iter = 184, accuracy (cur) = 0.720000 (all), 0.450000 (pos), 0.900000 (neg) | |
| iter = 184, accuracy (avg) = 0.573526 (all), 0.503102 (pos), 0.646695 (neg) | |
| data reader: epoch = 0, batch = 185 / 4040 | |
| iter = 185, cls_loss (cur) = 0.522064, cls_loss (avg) = 0.492499, lr = 0.010000 | |
| iter = 185, accuracy (cur) = 0.780000 (all), 0.600000 (pos), 0.960000 (neg) | |
| iter = 185, accuracy (avg) = 0.575591 (all), 0.504071 (pos), 0.649828 (neg) | |
| data reader: epoch = 0, batch = 186 / 4040 | |
| iter = 186, cls_loss (cur) = 0.542236, cls_loss (avg) = 0.492996, lr = 0.010000 | |
| iter = 186, accuracy (cur) = 0.760000 (all), 0.680000 (pos), 0.840000 (neg) | |
| iter = 186, accuracy (avg) = 0.577435 (all), 0.505830 (pos), 0.651730 (neg) | |
| data reader: epoch = 0, batch = 187 / 4040 | |
| iter = 187, cls_loss (cur) = 0.590602, cls_loss (avg) = 0.493972, lr = 0.010000 | |
| iter = 187, accuracy (cur) = 0.640000 (all), 0.482759 (pos), 0.857143 (neg) | |
| iter = 187, accuracy (avg) = 0.578061 (all), 0.505600 (pos), 0.653784 (neg) | |
| data reader: epoch = 0, batch = 188 / 4040 | |
| iter = 188, cls_loss (cur) = 0.592327, cls_loss (avg) = 0.494956, lr = 0.010000 | |
| iter = 188, accuracy (cur) = 0.680000 (all), 0.666667 (pos), 0.692308 (neg) | |
| iter = 188, accuracy (avg) = 0.579080 (all), 0.507210 (pos), 0.654169 (neg) | |
| data reader: epoch = 0, batch = 189 / 4040 | |
| iter = 189, cls_loss (cur) = 0.504039, cls_loss (avg) = 0.495047, lr = 0.010000 | |
| iter = 189, accuracy (cur) = 0.740000 (all), 0.791667 (pos), 0.692308 (neg) | |
| iter = 189, accuracy (avg) = 0.580689 (all), 0.510055 (pos), 0.654551 (neg) | |
| data reader: epoch = 0, batch = 190 / 4040 | |
| iter = 190, cls_loss (cur) = 0.538282, cls_loss (avg) = 0.495479, lr = 0.010000 | |
| iter = 190, accuracy (cur) = 0.720000 (all), 0.560000 (pos), 0.880000 (neg) | |
| iter = 190, accuracy (avg) = 0.582082 (all), 0.510554 (pos), 0.656805 (neg) | |
| data reader: epoch = 0, batch = 191 / 4040 | |
| iter = 191, cls_loss (cur) = 0.563953, cls_loss (avg) = 0.496164, lr = 0.010000 | |
| iter = 191, accuracy (cur) = 0.680000 (all), 0.521739 (pos), 0.814815 (neg) | |
| iter = 191, accuracy (avg) = 0.583062 (all), 0.510666 (pos), 0.658385 (neg) | |
| data reader: epoch = 0, batch = 192 / 4040 | |
| iter = 192, cls_loss (cur) = 0.498602, cls_loss (avg) = 0.496188, lr = 0.010000 | |
| iter = 192, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.827586 (neg) | |
| iter = 192, accuracy (avg) = 0.584831 (all), 0.512226 (pos), 0.660077 (neg) | |
| data reader: epoch = 0, batch = 193 / 4040 | |
| iter = 193, cls_loss (cur) = 0.653378, cls_loss (avg) = 0.497760, lr = 0.010000 | |
| iter = 193, accuracy (cur) = 0.600000 (all), 0.307692 (pos), 0.916667 (neg) | |
| iter = 193, accuracy (avg) = 0.584983 (all), 0.510181 (pos), 0.662643 (neg) | |
| data reader: epoch = 0, batch = 194 / 4040 | |
| iter = 194, cls_loss (cur) = 0.590534, cls_loss (avg) = 0.498688, lr = 0.010000 | |
| iter = 194, accuracy (cur) = 0.700000 (all), 0.523810 (pos), 0.827586 (neg) | |
| iter = 194, accuracy (avg) = 0.586133 (all), 0.510317 (pos), 0.664293 (neg) | |
| data reader: epoch = 0, batch = 195 / 4040 | |
| iter = 195, cls_loss (cur) = 0.647423, cls_loss (avg) = 0.500175, lr = 0.010000 | |
| iter = 195, accuracy (cur) = 0.600000 (all), 0.379310 (pos), 0.904762 (neg) | |
| iter = 195, accuracy (avg) = 0.586272 (all), 0.509007 (pos), 0.666697 (neg) | |
| data reader: epoch = 0, batch = 196 / 4040 | |
| iter = 196, cls_loss (cur) = 0.460739, cls_loss (avg) = 0.499781, lr = 0.010000 | |
| iter = 196, accuracy (cur) = 0.760000 (all), 0.740741 (pos), 0.782609 (neg) | |
| iter = 196, accuracy (avg) = 0.588009 (all), 0.511325 (pos), 0.667856 (neg) | |
| data reader: epoch = 0, batch = 197 / 4040 | |
| iter = 197, cls_loss (cur) = 0.483952, cls_loss (avg) = 0.499622, lr = 0.010000 | |
| iter = 197, accuracy (cur) = 0.720000 (all), 0.620690 (pos), 0.857143 (neg) | |
| iter = 197, accuracy (avg) = 0.589329 (all), 0.512418 (pos), 0.669749 (neg) | |
| data reader: epoch = 0, batch = 198 / 4040 | |
| iter = 198, cls_loss (cur) = 0.620668, cls_loss (avg) = 0.500833, lr = 0.010000 | |
| iter = 198, accuracy (cur) = 0.580000 (all), 0.440000 (pos), 0.720000 (neg) | |
| iter = 198, accuracy (avg) = 0.589235 (all), 0.511694 (pos), 0.670252 (neg) | |
| data reader: epoch = 0, batch = 199 / 4040 | |
| iter = 199, cls_loss (cur) = 0.584478, cls_loss (avg) = 0.501669, lr = 0.010000 | |
| iter = 199, accuracy (cur) = 0.700000 (all), 0.739130 (pos), 0.666667 (neg) | |
| iter = 199, accuracy (avg) = 0.590343 (all), 0.513968 (pos), 0.670216 (neg) | |
| data reader: epoch = 0, batch = 200 / 4040 | |
| iter = 200, cls_loss (cur) = 0.585956, cls_loss (avg) = 0.502512, lr = 0.010000 | |
| iter = 200, accuracy (cur) = 0.720000 (all), 0.782609 (pos), 0.666667 (neg) | |
| iter = 200, accuracy (avg) = 0.591640 (all), 0.516655 (pos), 0.670180 (neg) | |
| data reader: epoch = 0, batch = 201 / 4040 | |
| iter = 201, cls_loss (cur) = 0.589719, cls_loss (avg) = 0.503384, lr = 0.010000 | |
| iter = 201, accuracy (cur) = 0.700000 (all), 0.518519 (pos), 0.913043 (neg) | |
| iter = 201, accuracy (avg) = 0.592723 (all), 0.516673 (pos), 0.672609 (neg) | |
| data reader: epoch = 0, batch = 202 / 4040 | |
| iter = 202, cls_loss (cur) = 0.585222, cls_loss (avg) = 0.504203, lr = 0.010000 | |
| iter = 202, accuracy (cur) = 0.600000 (all), 0.448276 (pos), 0.809524 (neg) | |
| iter = 202, accuracy (avg) = 0.592796 (all), 0.515989 (pos), 0.673978 (neg) | |
| data reader: epoch = 0, batch = 203 / 4040 | |
| iter = 203, cls_loss (cur) = 0.573960, cls_loss (avg) = 0.504900, lr = 0.010000 | |
| iter = 203, accuracy (cur) = 0.640000 (all), 0.550000 (pos), 0.700000 (neg) | |
| iter = 203, accuracy (avg) = 0.593268 (all), 0.516330 (pos), 0.674238 (neg) | |
| data reader: epoch = 0, batch = 204 / 4040 | |
| iter = 204, cls_loss (cur) = 0.555711, cls_loss (avg) = 0.505408, lr = 0.010000 | |
| iter = 204, accuracy (cur) = 0.720000 (all), 0.576923 (pos), 0.875000 (neg) | |
| iter = 204, accuracy (avg) = 0.594535 (all), 0.516935 (pos), 0.676246 (neg) | |
| data reader: epoch = 0, batch = 205 / 4040 | |
| iter = 205, cls_loss (cur) = 0.630766, cls_loss (avg) = 0.506662, lr = 0.010000 | |
| iter = 205, accuracy (cur) = 0.600000 (all), 0.461538 (pos), 0.750000 (neg) | |
| iter = 205, accuracy (avg) = 0.594590 (all), 0.516381 (pos), 0.676984 (neg) | |
| data reader: epoch = 0, batch = 206 / 4040 | |
| iter = 206, cls_loss (cur) = 0.559651, cls_loss (avg) = 0.507192, lr = 0.010000 | |
| iter = 206, accuracy (cur) = 0.660000 (all), 0.615385 (pos), 0.708333 (neg) | |
| iter = 206, accuracy (avg) = 0.595244 (all), 0.517372 (pos), 0.677297 (neg) | |
| data reader: epoch = 0, batch = 207 / 4040 | |
| iter = 207, cls_loss (cur) = 0.558437, cls_loss (avg) = 0.507704, lr = 0.010000 | |
| iter = 207, accuracy (cur) = 0.700000 (all), 0.666667 (pos), 0.730769 (neg) | |
| iter = 207, accuracy (avg) = 0.596292 (all), 0.518864 (pos), 0.677832 (neg) | |
| data reader: epoch = 0, batch = 208 / 4040 | |
| iter = 208, cls_loss (cur) = 0.562305, cls_loss (avg) = 0.508250, lr = 0.010000 | |
| iter = 208, accuracy (cur) = 0.680000 (all), 0.407407 (pos), 1.000000 (neg) | |
| iter = 208, accuracy (avg) = 0.597129 (all), 0.517750 (pos), 0.681054 (neg) | |
| data reader: epoch = 0, batch = 209 / 4040 | |
| iter = 209, cls_loss (cur) = 0.516176, cls_loss (avg) = 0.508330, lr = 0.010000 | |
| iter = 209, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.826087 (neg) | |
| iter = 209, accuracy (avg) = 0.598557 (all), 0.519239 (pos), 0.682504 (neg) | |
| data reader: epoch = 0, batch = 210 / 4040 | |
| iter = 210, cls_loss (cur) = 0.590815, cls_loss (avg) = 0.509154, lr = 0.010000 | |
| iter = 210, accuracy (cur) = 0.680000 (all), 0.551724 (pos), 0.857143 (neg) | |
| iter = 210, accuracy (avg) = 0.599372 (all), 0.519564 (pos), 0.684250 (neg) | |
| data reader: epoch = 0, batch = 211 / 4040 | |
| iter = 211, cls_loss (cur) = 0.556219, cls_loss (avg) = 0.509625, lr = 0.010000 | |
| iter = 211, accuracy (cur) = 0.700000 (all), 0.652174 (pos), 0.740741 (neg) | |
| iter = 211, accuracy (avg) = 0.600378 (all), 0.520890 (pos), 0.684815 (neg) | |
| data reader: epoch = 0, batch = 212 / 4040 | |
| iter = 212, cls_loss (cur) = 0.602736, cls_loss (avg) = 0.510556, lr = 0.010000 | |
| iter = 212, accuracy (cur) = 0.640000 (all), 0.666667 (pos), 0.615385 (neg) | |
| iter = 212, accuracy (avg) = 0.600774 (all), 0.522348 (pos), 0.684121 (neg) | |
| data reader: epoch = 0, batch = 213 / 4040 | |
| iter = 213, cls_loss (cur) = 0.516549, cls_loss (avg) = 0.510616, lr = 0.010000 | |
| iter = 213, accuracy (cur) = 0.700000 (all), 0.571429 (pos), 0.863636 (neg) | |
| iter = 213, accuracy (avg) = 0.601767 (all), 0.522839 (pos), 0.685916 (neg) | |
| data reader: epoch = 0, batch = 214 / 4040 | |
| iter = 214, cls_loss (cur) = 0.624225, cls_loss (avg) = 0.511752, lr = 0.010000 | |
| iter = 214, accuracy (cur) = 0.620000 (all), 0.518519 (pos), 0.739130 (neg) | |
| iter = 214, accuracy (avg) = 0.601949 (all), 0.522795 (pos), 0.686448 (neg) | |
| data reader: epoch = 0, batch = 215 / 4040 | |
| iter = 215, cls_loss (cur) = 0.444855, cls_loss (avg) = 0.511083, lr = 0.010000 | |
| iter = 215, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 215, accuracy (avg) = 0.603929 (all), 0.525967 (pos), 0.687184 (neg) | |
| data reader: epoch = 0, batch = 216 / 4040 | |
| iter = 216, cls_loss (cur) = 0.501366, cls_loss (avg) = 0.510986, lr = 0.010000 | |
| iter = 216, accuracy (cur) = 0.760000 (all), 0.760000 (pos), 0.760000 (neg) | |
| iter = 216, accuracy (avg) = 0.605490 (all), 0.528308 (pos), 0.687912 (neg) | |
| data reader: epoch = 0, batch = 217 / 4040 | |
| iter = 217, cls_loss (cur) = 0.560117, cls_loss (avg) = 0.511477, lr = 0.010000 | |
| iter = 217, accuracy (cur) = 0.700000 (all), 0.565217 (pos), 0.814815 (neg) | |
| iter = 217, accuracy (avg) = 0.606435 (all), 0.528677 (pos), 0.689181 (neg) | |
| data reader: epoch = 0, batch = 218 / 4040 | |
| iter = 218, cls_loss (cur) = 0.532480, cls_loss (avg) = 0.511687, lr = 0.010000 | |
| iter = 218, accuracy (cur) = 0.740000 (all), 0.758621 (pos), 0.714286 (neg) | |
| iter = 218, accuracy (avg) = 0.607771 (all), 0.530976 (pos), 0.689432 (neg) | |
| data reader: epoch = 0, batch = 219 / 4040 | |
| iter = 219, cls_loss (cur) = 0.582982, cls_loss (avg) = 0.512400, lr = 0.010000 | |
| iter = 219, accuracy (cur) = 0.700000 (all), 0.583333 (pos), 0.807692 (neg) | |
| iter = 219, accuracy (avg) = 0.608693 (all), 0.531500 (pos), 0.690615 (neg) | |
| data reader: epoch = 0, batch = 220 / 4040 | |
| iter = 220, cls_loss (cur) = 0.559649, cls_loss (avg) = 0.512873, lr = 0.010000 | |
| iter = 220, accuracy (cur) = 0.760000 (all), 0.571429 (pos), 0.896552 (neg) | |
| iter = 220, accuracy (avg) = 0.610206 (all), 0.531899 (pos), 0.692674 (neg) | |
| data reader: epoch = 0, batch = 221 / 4040 | |
| iter = 221, cls_loss (cur) = 0.577218, cls_loss (avg) = 0.513516, lr = 0.010000 | |
| iter = 221, accuracy (cur) = 0.620000 (all), 0.464286 (pos), 0.818182 (neg) | |
| iter = 221, accuracy (avg) = 0.610304 (all), 0.531223 (pos), 0.693929 (neg) | |
| data reader: epoch = 0, batch = 222 / 4040 | |
| iter = 222, cls_loss (cur) = 0.500120, cls_loss (avg) = 0.513382, lr = 0.010000 | |
| iter = 222, accuracy (cur) = 0.760000 (all), 0.687500 (pos), 0.888889 (neg) | |
| iter = 222, accuracy (avg) = 0.611801 (all), 0.532786 (pos), 0.695879 (neg) | |
| data reader: epoch = 0, batch = 223 / 4040 | |
| iter = 223, cls_loss (cur) = 0.515118, cls_loss (avg) = 0.513400, lr = 0.010000 | |
| iter = 223, accuracy (cur) = 0.760000 (all), 0.760000 (pos), 0.760000 (neg) | |
| iter = 223, accuracy (avg) = 0.613283 (all), 0.535058 (pos), 0.696520 (neg) | |
| data reader: epoch = 0, batch = 224 / 4040 | |
| iter = 224, cls_loss (cur) = 0.599452, cls_loss (avg) = 0.514260, lr = 0.010000 | |
| iter = 224, accuracy (cur) = 0.700000 (all), 0.640000 (pos), 0.760000 (neg) | |
| iter = 224, accuracy (avg) = 0.614150 (all), 0.536107 (pos), 0.697155 (neg) | |
| data reader: epoch = 0, batch = 225 / 4040 | |
| iter = 225, cls_loss (cur) = 0.512830, cls_loss (avg) = 0.514246, lr = 0.010000 | |
| iter = 225, accuracy (cur) = 0.780000 (all), 0.590909 (pos), 0.928571 (neg) | |
| iter = 225, accuracy (avg) = 0.615809 (all), 0.536655 (pos), 0.699469 (neg) | |
| data reader: epoch = 0, batch = 226 / 4040 | |
| iter = 226, cls_loss (cur) = 0.606269, cls_loss (avg) = 0.515166, lr = 0.010000 | |
| iter = 226, accuracy (cur) = 0.680000 (all), 0.434783 (pos), 0.888889 (neg) | |
| iter = 226, accuracy (avg) = 0.616451 (all), 0.535637 (pos), 0.701363 (neg) | |
| data reader: epoch = 0, batch = 227 / 4040 | |
| iter = 227, cls_loss (cur) = 0.568390, cls_loss (avg) = 0.515698, lr = 0.010000 | |
| iter = 227, accuracy (cur) = 0.680000 (all), 0.450000 (pos), 0.833333 (neg) | |
| iter = 227, accuracy (avg) = 0.617086 (all), 0.534780 (pos), 0.702683 (neg) | |
| data reader: epoch = 0, batch = 228 / 4040 | |
| iter = 228, cls_loss (cur) = 0.601569, cls_loss (avg) = 0.516557, lr = 0.010000 | |
| iter = 228, accuracy (cur) = 0.640000 (all), 0.478261 (pos), 0.777778 (neg) | |
| iter = 228, accuracy (avg) = 0.617315 (all), 0.534215 (pos), 0.703434 (neg) | |
| data reader: epoch = 0, batch = 229 / 4040 | |
| iter = 229, cls_loss (cur) = 0.589360, cls_loss (avg) = 0.517285, lr = 0.010000 | |
| iter = 229, accuracy (cur) = 0.700000 (all), 0.566667 (pos), 0.900000 (neg) | |
| iter = 229, accuracy (avg) = 0.618142 (all), 0.534540 (pos), 0.705399 (neg) | |
| data reader: epoch = 0, batch = 230 / 4040 | |
| iter = 230, cls_loss (cur) = 0.508591, cls_loss (avg) = 0.517198, lr = 0.010000 | |
| iter = 230, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.812500 (neg) | |
| iter = 230, accuracy (avg) = 0.619561 (all), 0.535861 (pos), 0.706470 (neg) | |
| data reader: epoch = 0, batch = 231 / 4040 | |
| iter = 231, cls_loss (cur) = 0.469658, cls_loss (avg) = 0.516723, lr = 0.010000 | |
| iter = 231, accuracy (cur) = 0.800000 (all), 0.708333 (pos), 0.884615 (neg) | |
| iter = 231, accuracy (avg) = 0.621365 (all), 0.537586 (pos), 0.708252 (neg) | |
| data reader: epoch = 0, batch = 232 / 4040 | |
| iter = 232, cls_loss (cur) = 0.507055, cls_loss (avg) = 0.516626, lr = 0.010000 | |
| iter = 232, accuracy (cur) = 0.800000 (all), 0.700000 (pos), 0.866667 (neg) | |
| iter = 232, accuracy (avg) = 0.623152 (all), 0.539210 (pos), 0.709836 (neg) | |
| data reader: epoch = 0, batch = 233 / 4040 | |
| iter = 233, cls_loss (cur) = 0.592029, cls_loss (avg) = 0.517380, lr = 0.010000 | |
| iter = 233, accuracy (cur) = 0.660000 (all), 0.629630 (pos), 0.695652 (neg) | |
| iter = 233, accuracy (avg) = 0.623520 (all), 0.540114 (pos), 0.709694 (neg) | |
| data reader: epoch = 0, batch = 234 / 4040 | |
| iter = 234, cls_loss (cur) = 0.486176, cls_loss (avg) = 0.517068, lr = 0.010000 | |
| iter = 234, accuracy (cur) = 0.760000 (all), 0.500000 (pos), 0.964286 (neg) | |
| iter = 234, accuracy (avg) = 0.624885 (all), 0.539713 (pos), 0.712240 (neg) | |
| data reader: epoch = 0, batch = 235 / 4040 | |
| iter = 235, cls_loss (cur) = 0.533284, cls_loss (avg) = 0.517230, lr = 0.010000 | |
| iter = 235, accuracy (cur) = 0.680000 (all), 0.565217 (pos), 0.777778 (neg) | |
| iter = 235, accuracy (avg) = 0.625436 (all), 0.539968 (pos), 0.712895 (neg) | |
| data reader: epoch = 0, batch = 236 / 4040 | |
| iter = 236, cls_loss (cur) = 0.563526, cls_loss (avg) = 0.517693, lr = 0.010000 | |
| iter = 236, accuracy (cur) = 0.720000 (all), 0.520000 (pos), 0.920000 (neg) | |
| iter = 236, accuracy (avg) = 0.626382 (all), 0.539768 (pos), 0.714966 (neg) | |
| data reader: epoch = 0, batch = 237 / 4040 | |
| iter = 237, cls_loss (cur) = 0.423277, cls_loss (avg) = 0.516749, lr = 0.010000 | |
| iter = 237, accuracy (cur) = 0.860000 (all), 0.925926 (pos), 0.782609 (neg) | |
| iter = 237, accuracy (avg) = 0.628718 (all), 0.543630 (pos), 0.715643 (neg) | |
| data reader: epoch = 0, batch = 238 / 4040 | |
| iter = 238, cls_loss (cur) = 0.588166, cls_loss (avg) = 0.517463, lr = 0.010000 | |
| iter = 238, accuracy (cur) = 0.620000 (all), 0.607143 (pos), 0.636364 (neg) | |
| iter = 238, accuracy (avg) = 0.628631 (all), 0.544265 (pos), 0.714850 (neg) | |
| data reader: epoch = 0, batch = 239 / 4040 | |
| iter = 239, cls_loss (cur) = 0.527469, cls_loss (avg) = 0.517563, lr = 0.010000 | |
| iter = 239, accuracy (cur) = 0.740000 (all), 0.550000 (pos), 0.866667 (neg) | |
| iter = 239, accuracy (avg) = 0.629744 (all), 0.544322 (pos), 0.716368 (neg) | |
| data reader: epoch = 0, batch = 240 / 4040 | |
| iter = 240, cls_loss (cur) = 0.502445, cls_loss (avg) = 0.517412, lr = 0.010000 | |
| iter = 240, accuracy (cur) = 0.780000 (all), 0.714286 (pos), 0.863636 (neg) | |
| iter = 240, accuracy (avg) = 0.631247 (all), 0.546022 (pos), 0.717841 (neg) | |
| data reader: epoch = 0, batch = 241 / 4040 | |
| iter = 241, cls_loss (cur) = 0.555199, cls_loss (avg) = 0.517790, lr = 0.010000 | |
| iter = 241, accuracy (cur) = 0.660000 (all), 0.576923 (pos), 0.750000 (neg) | |
| iter = 241, accuracy (avg) = 0.631534 (all), 0.546331 (pos), 0.718162 (neg) | |
| data reader: epoch = 0, batch = 242 / 4040 | |
| iter = 242, cls_loss (cur) = 0.532932, cls_loss (avg) = 0.517941, lr = 0.010000 | |
| iter = 242, accuracy (cur) = 0.720000 (all), 0.653846 (pos), 0.791667 (neg) | |
| iter = 242, accuracy (avg) = 0.632419 (all), 0.547406 (pos), 0.718897 (neg) | |
| data reader: epoch = 0, batch = 243 / 4040 | |
| iter = 243, cls_loss (cur) = 0.534544, cls_loss (avg) = 0.518107, lr = 0.010000 | |
| iter = 243, accuracy (cur) = 0.700000 (all), 0.625000 (pos), 0.769231 (neg) | |
| iter = 243, accuracy (avg) = 0.633095 (all), 0.548182 (pos), 0.719401 (neg) | |
| data reader: epoch = 0, batch = 244 / 4040 | |
| iter = 244, cls_loss (cur) = 0.503072, cls_loss (avg) = 0.517957, lr = 0.010000 | |
| iter = 244, accuracy (cur) = 0.780000 (all), 0.680000 (pos), 0.880000 (neg) | |
| iter = 244, accuracy (avg) = 0.634564 (all), 0.549500 (pos), 0.721007 (neg) | |
| data reader: epoch = 0, batch = 245 / 4040 | |
| iter = 245, cls_loss (cur) = 0.449324, cls_loss (avg) = 0.517271, lr = 0.010000 | |
| iter = 245, accuracy (cur) = 0.760000 (all), 0.689655 (pos), 0.857143 (neg) | |
| iter = 245, accuracy (avg) = 0.635818 (all), 0.550902 (pos), 0.722368 (neg) | |
| data reader: epoch = 0, batch = 246 / 4040 | |
| iter = 246, cls_loss (cur) = 0.554207, cls_loss (avg) = 0.517640, lr = 0.010000 | |
| iter = 246, accuracy (cur) = 0.700000 (all), 0.629630 (pos), 0.782609 (neg) | |
| iter = 246, accuracy (avg) = 0.636460 (all), 0.551689 (pos), 0.722971 (neg) | |
| data reader: epoch = 0, batch = 247 / 4040 | |
| iter = 247, cls_loss (cur) = 0.478633, cls_loss (avg) = 0.517250, lr = 0.010000 | |
| iter = 247, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 247, accuracy (avg) = 0.638296 (all), 0.553129 (pos), 0.725000 (neg) | |
| data reader: epoch = 0, batch = 248 / 4040 | |
| iter = 248, cls_loss (cur) = 0.489012, cls_loss (avg) = 0.516968, lr = 0.010000 | |
| iter = 248, accuracy (cur) = 0.800000 (all), 0.703704 (pos), 0.913043 (neg) | |
| iter = 248, accuracy (avg) = 0.639913 (all), 0.554634 (pos), 0.726881 (neg) | |
| data reader: epoch = 0, batch = 249 / 4040 | |
| iter = 249, cls_loss (cur) = 0.541254, cls_loss (avg) = 0.517210, lr = 0.010000 | |
| iter = 249, accuracy (cur) = 0.700000 (all), 0.666667 (pos), 0.739130 (neg) | |
| iter = 249, accuracy (avg) = 0.640513 (all), 0.555755 (pos), 0.727003 (neg) | |
| data reader: epoch = 0, batch = 250 / 4040 | |
| iter = 250, cls_loss (cur) = 0.531431, cls_loss (avg) = 0.517353, lr = 0.010000 | |
| iter = 250, accuracy (cur) = 0.740000 (all), 0.608696 (pos), 0.851852 (neg) | |
| iter = 250, accuracy (avg) = 0.641508 (all), 0.556284 (pos), 0.728252 (neg) | |
| data reader: epoch = 0, batch = 251 / 4040 | |
| iter = 251, cls_loss (cur) = 0.485399, cls_loss (avg) = 0.517033, lr = 0.010000 | |
| iter = 251, accuracy (cur) = 0.780000 (all), 0.720000 (pos), 0.840000 (neg) | |
| iter = 251, accuracy (avg) = 0.642893 (all), 0.557921 (pos), 0.729369 (neg) | |
| data reader: epoch = 0, batch = 252 / 4040 | |
| iter = 252, cls_loss (cur) = 0.570549, cls_loss (avg) = 0.517568, lr = 0.010000 | |
| iter = 252, accuracy (cur) = 0.700000 (all), 0.629630 (pos), 0.782609 (neg) | |
| iter = 252, accuracy (avg) = 0.643464 (all), 0.558638 (pos), 0.729901 (neg) | |
| data reader: epoch = 0, batch = 253 / 4040 | |
| iter = 253, cls_loss (cur) = 0.651713, cls_loss (avg) = 0.518910, lr = 0.010000 | |
| iter = 253, accuracy (cur) = 0.580000 (all), 0.346154 (pos), 0.833333 (neg) | |
| iter = 253, accuracy (avg) = 0.642830 (all), 0.556513 (pos), 0.730936 (neg) | |
| data reader: epoch = 0, batch = 254 / 4040 | |
| iter = 254, cls_loss (cur) = 0.576757, cls_loss (avg) = 0.519488, lr = 0.010000 | |
| iter = 254, accuracy (cur) = 0.680000 (all), 0.555556 (pos), 0.826087 (neg) | |
| iter = 254, accuracy (avg) = 0.643201 (all), 0.556504 (pos), 0.731887 (neg) | |
| data reader: epoch = 0, batch = 255 / 4040 | |
| iter = 255, cls_loss (cur) = 0.589090, cls_loss (avg) = 0.520184, lr = 0.010000 | |
| iter = 255, accuracy (cur) = 0.660000 (all), 0.652174 (pos), 0.666667 (neg) | |
| iter = 255, accuracy (avg) = 0.643369 (all), 0.557461 (pos), 0.731235 (neg) | |
| data reader: epoch = 0, batch = 256 / 4040 | |
| iter = 256, cls_loss (cur) = 0.523487, cls_loss (avg) = 0.520217, lr = 0.010000 | |
| iter = 256, accuracy (cur) = 0.720000 (all), 0.560000 (pos), 0.880000 (neg) | |
| iter = 256, accuracy (avg) = 0.644136 (all), 0.557486 (pos), 0.732723 (neg) | |
| data reader: epoch = 0, batch = 257 / 4040 | |
| iter = 257, cls_loss (cur) = 0.562116, cls_loss (avg) = 0.520636, lr = 0.010000 | |
| iter = 257, accuracy (cur) = 0.700000 (all), 0.592593 (pos), 0.826087 (neg) | |
| iter = 257, accuracy (avg) = 0.644694 (all), 0.557837 (pos), 0.733656 (neg) | |
| data reader: epoch = 0, batch = 258 / 4040 | |
| iter = 258, cls_loss (cur) = 0.566483, cls_loss (avg) = 0.521095, lr = 0.010000 | |
| iter = 258, accuracy (cur) = 0.720000 (all), 0.550000 (pos), 0.833333 (neg) | |
| iter = 258, accuracy (avg) = 0.645447 (all), 0.557759 (pos), 0.734653 (neg) | |
| data reader: epoch = 0, batch = 259 / 4040 | |
| iter = 259, cls_loss (cur) = 0.493859, cls_loss (avg) = 0.520822, lr = 0.010000 | |
| iter = 259, accuracy (cur) = 0.780000 (all), 0.583333 (pos), 0.961538 (neg) | |
| iter = 259, accuracy (avg) = 0.646793 (all), 0.558014 (pos), 0.736922 (neg) | |
| data reader: epoch = 0, batch = 260 / 4040 | |
| iter = 260, cls_loss (cur) = 0.445776, cls_loss (avg) = 0.520072, lr = 0.010000 | |
| iter = 260, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 260, accuracy (avg) = 0.648725 (all), 0.560434 (pos), 0.738353 (neg) | |
| data reader: epoch = 0, batch = 261 / 4040 | |
| iter = 261, cls_loss (cur) = 0.456387, cls_loss (avg) = 0.519435, lr = 0.010000 | |
| iter = 261, accuracy (cur) = 0.820000 (all), 0.809524 (pos), 0.827586 (neg) | |
| iter = 261, accuracy (avg) = 0.650438 (all), 0.562925 (pos), 0.739245 (neg) | |
| data reader: epoch = 0, batch = 262 / 4040 | |
| iter = 262, cls_loss (cur) = 0.542482, cls_loss (avg) = 0.519665, lr = 0.010000 | |
| iter = 262, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 0.884615 (neg) | |
| iter = 262, accuracy (avg) = 0.650933 (all), 0.562296 (pos), 0.740699 (neg) | |
| data reader: epoch = 0, batch = 263 / 4040 | |
| iter = 263, cls_loss (cur) = 0.520141, cls_loss (avg) = 0.519670, lr = 0.010000 | |
| iter = 263, accuracy (cur) = 0.740000 (all), 0.565217 (pos), 0.888889 (neg) | |
| iter = 263, accuracy (avg) = 0.651824 (all), 0.562325 (pos), 0.742181 (neg) | |
| data reader: epoch = 0, batch = 264 / 4040 | |
| iter = 264, cls_loss (cur) = 0.500591, cls_loss (avg) = 0.519479, lr = 0.010000 | |
| iter = 264, accuracy (cur) = 0.760000 (all), 0.678571 (pos), 0.863636 (neg) | |
| iter = 264, accuracy (avg) = 0.652906 (all), 0.563488 (pos), 0.743395 (neg) | |
| data reader: epoch = 0, batch = 265 / 4040 | |
| iter = 265, cls_loss (cur) = 0.646158, cls_loss (avg) = 0.520746, lr = 0.010000 | |
| iter = 265, accuracy (cur) = 0.580000 (all), 0.523810 (pos), 0.620690 (neg) | |
| iter = 265, accuracy (avg) = 0.652177 (all), 0.563091 (pos), 0.742168 (neg) | |
| data reader: epoch = 0, batch = 266 / 4040 | |
| iter = 266, cls_loss (cur) = 0.460289, cls_loss (avg) = 0.520142, lr = 0.010000 | |
| iter = 266, accuracy (cur) = 0.800000 (all), 0.583333 (pos), 1.000000 (neg) | |
| iter = 266, accuracy (avg) = 0.653655 (all), 0.563293 (pos), 0.744747 (neg) | |
| data reader: epoch = 0, batch = 267 / 4040 | |
| iter = 267, cls_loss (cur) = 0.608348, cls_loss (avg) = 0.521024, lr = 0.010000 | |
| iter = 267, accuracy (cur) = 0.580000 (all), 0.357143 (pos), 0.863636 (neg) | |
| iter = 267, accuracy (avg) = 0.652918 (all), 0.561232 (pos), 0.745935 (neg) | |
| data reader: epoch = 0, batch = 268 / 4040 | |
| iter = 268, cls_loss (cur) = 0.507614, cls_loss (avg) = 0.520890, lr = 0.010000 | |
| iter = 268, accuracy (cur) = 0.740000 (all), 0.733333 (pos), 0.750000 (neg) | |
| iter = 268, accuracy (avg) = 0.653789 (all), 0.562953 (pos), 0.745976 (neg) | |
| data reader: epoch = 0, batch = 269 / 4040 | |
| iter = 269, cls_loss (cur) = 0.646978, cls_loss (avg) = 0.522150, lr = 0.010000 | |
| iter = 269, accuracy (cur) = 0.580000 (all), 0.576923 (pos), 0.583333 (neg) | |
| iter = 269, accuracy (avg) = 0.653051 (all), 0.563092 (pos), 0.744350 (neg) | |
| data reader: epoch = 0, batch = 270 / 4040 | |
| iter = 270, cls_loss (cur) = 0.498437, cls_loss (avg) = 0.521913, lr = 0.010000 | |
| iter = 270, accuracy (cur) = 0.640000 (all), 0.740741 (pos), 0.521739 (neg) | |
| iter = 270, accuracy (avg) = 0.652921 (all), 0.564869 (pos), 0.742124 (neg) | |
| data reader: epoch = 0, batch = 271 / 4040 | |
| iter = 271, cls_loss (cur) = 0.563543, cls_loss (avg) = 0.522330, lr = 0.010000 | |
| iter = 271, accuracy (cur) = 0.660000 (all), 0.583333 (pos), 0.730769 (neg) | |
| iter = 271, accuracy (avg) = 0.652992 (all), 0.565054 (pos), 0.742010 (neg) | |
| data reader: epoch = 0, batch = 272 / 4040 | |
| iter = 272, cls_loss (cur) = 0.582675, cls_loss (avg) = 0.522933, lr = 0.010000 | |
| iter = 272, accuracy (cur) = 0.640000 (all), 0.640000 (pos), 0.640000 (neg) | |
| iter = 272, accuracy (avg) = 0.652862 (all), 0.565803 (pos), 0.740990 (neg) | |
| data reader: epoch = 0, batch = 273 / 4040 | |
| iter = 273, cls_loss (cur) = 0.573291, cls_loss (avg) = 0.523437, lr = 0.010000 | |
| iter = 273, accuracy (cur) = 0.720000 (all), 0.523810 (pos), 0.862069 (neg) | |
| iter = 273, accuracy (avg) = 0.653533 (all), 0.565383 (pos), 0.742201 (neg) | |
| data reader: epoch = 0, batch = 274 / 4040 | |
| iter = 274, cls_loss (cur) = 0.553563, cls_loss (avg) = 0.523738, lr = 0.010000 | |
| iter = 274, accuracy (cur) = 0.660000 (all), 0.500000 (pos), 0.833333 (neg) | |
| iter = 274, accuracy (avg) = 0.653598 (all), 0.564729 (pos), 0.743112 (neg) | |
| data reader: epoch = 0, batch = 275 / 4040 | |
| iter = 275, cls_loss (cur) = 0.542592, cls_loss (avg) = 0.523926, lr = 0.010000 | |
| iter = 275, accuracy (cur) = 0.760000 (all), 0.615385 (pos), 0.916667 (neg) | |
| iter = 275, accuracy (avg) = 0.654662 (all), 0.565236 (pos), 0.744848 (neg) | |
| data reader: epoch = 0, batch = 276 / 4040 | |
| iter = 276, cls_loss (cur) = 0.466013, cls_loss (avg) = 0.523347, lr = 0.010000 | |
| iter = 276, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 276, accuracy (avg) = 0.656315 (all), 0.567410 (pos), 0.745918 (neg) | |
| data reader: epoch = 0, batch = 277 / 4040 | |
| iter = 277, cls_loss (cur) = 0.560982, cls_loss (avg) = 0.523724, lr = 0.010000 | |
| iter = 277, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.827586 (neg) | |
| iter = 277, accuracy (avg) = 0.657352 (all), 0.568402 (pos), 0.746734 (neg) | |
| data reader: epoch = 0, batch = 278 / 4040 | |
| iter = 278, cls_loss (cur) = 0.519836, cls_loss (avg) = 0.523685, lr = 0.010000 | |
| iter = 278, accuracy (cur) = 0.720000 (all), 0.551724 (pos), 0.952381 (neg) | |
| iter = 278, accuracy (avg) = 0.657978 (all), 0.568235 (pos), 0.748791 (neg) | |
| data reader: epoch = 0, batch = 279 / 4040 | |
| iter = 279, cls_loss (cur) = 0.549526, cls_loss (avg) = 0.523943, lr = 0.010000 | |
| iter = 279, accuracy (cur) = 0.800000 (all), 0.684211 (pos), 0.870968 (neg) | |
| iter = 279, accuracy (avg) = 0.659399 (all), 0.569395 (pos), 0.750013 (neg) | |
| data reader: epoch = 0, batch = 280 / 4040 | |
| iter = 280, cls_loss (cur) = 0.395130, cls_loss (avg) = 0.522655, lr = 0.010000 | |
| iter = 280, accuracy (cur) = 0.900000 (all), 0.826087 (pos), 0.962963 (neg) | |
| iter = 280, accuracy (avg) = 0.661805 (all), 0.571962 (pos), 0.752142 (neg) | |
| data reader: epoch = 0, batch = 281 / 4040 | |
| iter = 281, cls_loss (cur) = 0.522177, cls_loss (avg) = 0.522650, lr = 0.010000 | |
| iter = 281, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 0.884615 (neg) | |
| iter = 281, accuracy (avg) = 0.662187 (all), 0.571242 (pos), 0.753467 (neg) | |
| data reader: epoch = 0, batch = 282 / 4040 | |
| iter = 282, cls_loss (cur) = 0.536935, cls_loss (avg) = 0.522793, lr = 0.010000 | |
| iter = 282, accuracy (cur) = 0.740000 (all), 0.500000 (pos), 0.852941 (neg) | |
| iter = 282, accuracy (avg) = 0.662965 (all), 0.570530 (pos), 0.754461 (neg) | |
| data reader: epoch = 0, batch = 283 / 4040 | |
| iter = 283, cls_loss (cur) = 0.528249, cls_loss (avg) = 0.522848, lr = 0.010000 | |
| iter = 283, accuracy (cur) = 0.700000 (all), 0.608696 (pos), 0.777778 (neg) | |
| iter = 283, accuracy (avg) = 0.663335 (all), 0.570912 (pos), 0.754695 (neg) | |
| data reader: epoch = 0, batch = 284 / 4040 | |
| iter = 284, cls_loss (cur) = 0.575166, cls_loss (avg) = 0.523371, lr = 0.010000 | |
| iter = 284, accuracy (cur) = 0.700000 (all), 0.555556 (pos), 0.869565 (neg) | |
| iter = 284, accuracy (avg) = 0.663702 (all), 0.570758 (pos), 0.755843 (neg) | |
| data reader: epoch = 0, batch = 285 / 4040 | |
| iter = 285, cls_loss (cur) = 0.535776, cls_loss (avg) = 0.523495, lr = 0.010000 | |
| iter = 285, accuracy (cur) = 0.700000 (all), 0.629630 (pos), 0.782609 (neg) | |
| iter = 285, accuracy (avg) = 0.664065 (all), 0.571347 (pos), 0.756111 (neg) | |
| data reader: epoch = 0, batch = 286 / 4040 | |
| iter = 286, cls_loss (cur) = 0.592575, cls_loss (avg) = 0.524186, lr = 0.010000 | |
| iter = 286, accuracy (cur) = 0.660000 (all), 0.571429 (pos), 0.772727 (neg) | |
| iter = 286, accuracy (avg) = 0.664024 (all), 0.571348 (pos), 0.756277 (neg) | |
| data reader: epoch = 0, batch = 287 / 4040 | |
| iter = 287, cls_loss (cur) = 0.503726, cls_loss (avg) = 0.523981, lr = 0.010000 | |
| iter = 287, accuracy (cur) = 0.800000 (all), 0.777778 (pos), 0.812500 (neg) | |
| iter = 287, accuracy (avg) = 0.665384 (all), 0.573412 (pos), 0.756839 (neg) | |
| data reader: epoch = 0, batch = 288 / 4040 | |
| iter = 288, cls_loss (cur) = 0.400639, cls_loss (avg) = 0.522748, lr = 0.010000 | |
| iter = 288, accuracy (cur) = 0.860000 (all), 0.739130 (pos), 0.962963 (neg) | |
| iter = 288, accuracy (avg) = 0.667330 (all), 0.575069 (pos), 0.758901 (neg) | |
| data reader: epoch = 0, batch = 289 / 4040 | |
| iter = 289, cls_loss (cur) = 0.472280, cls_loss (avg) = 0.522243, lr = 0.010000 | |
| iter = 289, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.843750 (neg) | |
| iter = 289, accuracy (avg) = 0.668457 (all), 0.575985 (pos), 0.759749 (neg) | |
| data reader: epoch = 0, batch = 290 / 4040 | |
| iter = 290, cls_loss (cur) = 0.572928, cls_loss (avg) = 0.522750, lr = 0.010000 | |
| iter = 290, accuracy (cur) = 0.660000 (all), 0.428571 (pos), 0.954545 (neg) | |
| iter = 290, accuracy (avg) = 0.668372 (all), 0.574511 (pos), 0.761697 (neg) | |
| data reader: epoch = 0, batch = 291 / 4040 | |
| iter = 291, cls_loss (cur) = 0.497065, cls_loss (avg) = 0.522493, lr = 0.010000 | |
| iter = 291, accuracy (cur) = 0.780000 (all), 0.680000 (pos), 0.880000 (neg) | |
| iter = 291, accuracy (avg) = 0.669488 (all), 0.575566 (pos), 0.762880 (neg) | |
| data reader: epoch = 0, batch = 292 / 4040 | |
| iter = 292, cls_loss (cur) = 0.543225, cls_loss (avg) = 0.522700, lr = 0.010000 | |
| iter = 292, accuracy (cur) = 0.700000 (all), 0.600000 (pos), 0.800000 (neg) | |
| iter = 292, accuracy (avg) = 0.669794 (all), 0.575810 (pos), 0.763251 (neg) | |
| data reader: epoch = 0, batch = 293 / 4040 | |
| iter = 293, cls_loss (cur) = 0.636813, cls_loss (avg) = 0.523842, lr = 0.010000 | |
| iter = 293, accuracy (cur) = 0.660000 (all), 0.523810 (pos), 0.758621 (neg) | |
| iter = 293, accuracy (avg) = 0.669696 (all), 0.575290 (pos), 0.763205 (neg) | |
| data reader: epoch = 0, batch = 294 / 4040 | |
| iter = 294, cls_loss (cur) = 0.428636, cls_loss (avg) = 0.522889, lr = 0.010000 | |
| iter = 294, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 294, accuracy (avg) = 0.671199 (all), 0.576494 (pos), 0.764832 (neg) | |
| data reader: epoch = 0, batch = 295 / 4040 | |
| iter = 295, cls_loss (cur) = 0.573561, cls_loss (avg) = 0.523396, lr = 0.010000 | |
| iter = 295, accuracy (cur) = 0.720000 (all), 0.555556 (pos), 0.913043 (neg) | |
| iter = 295, accuracy (avg) = 0.671687 (all), 0.576284 (pos), 0.766314 (neg) | |
| data reader: epoch = 0, batch = 296 / 4040 | |
| iter = 296, cls_loss (cur) = 0.490949, cls_loss (avg) = 0.523072, lr = 0.010000 | |
| iter = 296, accuracy (cur) = 0.800000 (all), 0.769231 (pos), 0.833333 (neg) | |
| iter = 296, accuracy (avg) = 0.672970 (all), 0.578214 (pos), 0.766985 (neg) | |
| data reader: epoch = 0, batch = 297 / 4040 | |
| iter = 297, cls_loss (cur) = 0.572901, cls_loss (avg) = 0.523570, lr = 0.010000 | |
| iter = 297, accuracy (cur) = 0.700000 (all), 0.703704 (pos), 0.695652 (neg) | |
| iter = 297, accuracy (avg) = 0.673240 (all), 0.579469 (pos), 0.766271 (neg) | |
| data reader: epoch = 0, batch = 298 / 4040 | |
| iter = 298, cls_loss (cur) = 0.526673, cls_loss (avg) = 0.523601, lr = 0.010000 | |
| iter = 298, accuracy (cur) = 0.800000 (all), 0.782609 (pos), 0.814815 (neg) | |
| iter = 298, accuracy (avg) = 0.674508 (all), 0.581500 (pos), 0.766757 (neg) | |
| data reader: epoch = 0, batch = 299 / 4040 | |
| iter = 299, cls_loss (cur) = 0.551742, cls_loss (avg) = 0.523882, lr = 0.010000 | |
| iter = 299, accuracy (cur) = 0.760000 (all), 0.750000 (pos), 0.769231 (neg) | |
| iter = 299, accuracy (avg) = 0.675363 (all), 0.583185 (pos), 0.766781 (neg) | |
| data reader: epoch = 0, batch = 300 / 4040 | |
| iter = 300, cls_loss (cur) = 0.507006, cls_loss (avg) = 0.523714, lr = 0.010000 | |
| iter = 300, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.884615 (neg) | |
| iter = 300, accuracy (avg) = 0.676409 (all), 0.584020 (pos), 0.767960 (neg) | |
| data reader: epoch = 0, batch = 301 / 4040 | |
| iter = 301, cls_loss (cur) = 0.549898, cls_loss (avg) = 0.523976, lr = 0.010000 | |
| iter = 301, accuracy (cur) = 0.740000 (all), 0.680000 (pos), 0.800000 (neg) | |
| iter = 301, accuracy (avg) = 0.677045 (all), 0.584980 (pos), 0.768280 (neg) | |
| data reader: epoch = 0, batch = 302 / 4040 | |
| iter = 302, cls_loss (cur) = 0.497095, cls_loss (avg) = 0.523707, lr = 0.010000 | |
| iter = 302, accuracy (cur) = 0.720000 (all), 0.758621 (pos), 0.666667 (neg) | |
| iter = 302, accuracy (avg) = 0.677474 (all), 0.586716 (pos), 0.767264 (neg) | |
| data reader: epoch = 0, batch = 303 / 4040 | |
| iter = 303, cls_loss (cur) = 0.530322, cls_loss (avg) = 0.523773, lr = 0.010000 | |
| iter = 303, accuracy (cur) = 0.740000 (all), 0.571429 (pos), 0.862069 (neg) | |
| iter = 303, accuracy (avg) = 0.678100 (all), 0.586563 (pos), 0.768212 (neg) | |
| data reader: epoch = 0, batch = 304 / 4040 | |
| iter = 304, cls_loss (cur) = 0.502574, cls_loss (avg) = 0.523561, lr = 0.010000 | |
| iter = 304, accuracy (cur) = 0.780000 (all), 0.681818 (pos), 0.857143 (neg) | |
| iter = 304, accuracy (avg) = 0.679119 (all), 0.587516 (pos), 0.769101 (neg) | |
| data reader: epoch = 0, batch = 305 / 4040 | |
| iter = 305, cls_loss (cur) = 0.595167, cls_loss (avg) = 0.524277, lr = 0.010000 | |
| iter = 305, accuracy (cur) = 0.640000 (all), 0.541667 (pos), 0.730769 (neg) | |
| iter = 305, accuracy (avg) = 0.678728 (all), 0.587057 (pos), 0.768718 (neg) | |
| data reader: epoch = 0, batch = 306 / 4040 | |
| iter = 306, cls_loss (cur) = 0.491988, cls_loss (avg) = 0.523954, lr = 0.010000 | |
| iter = 306, accuracy (cur) = 0.800000 (all), 0.615385 (pos), 1.000000 (neg) | |
| iter = 306, accuracy (avg) = 0.679940 (all), 0.587341 (pos), 0.771031 (neg) | |
| data reader: epoch = 0, batch = 307 / 4040 | |
| iter = 307, cls_loss (cur) = 0.463689, cls_loss (avg) = 0.523351, lr = 0.010000 | |
| iter = 307, accuracy (cur) = 0.820000 (all), 0.809524 (pos), 0.827586 (neg) | |
| iter = 307, accuracy (avg) = 0.681341 (all), 0.589562 (pos), 0.771596 (neg) | |
| data reader: epoch = 0, batch = 308 / 4040 | |
| iter = 308, cls_loss (cur) = 0.521532, cls_loss (avg) = 0.523333, lr = 0.010000 | |
| iter = 308, accuracy (cur) = 0.740000 (all), 0.642857 (pos), 0.863636 (neg) | |
| iter = 308, accuracy (avg) = 0.681927 (all), 0.590095 (pos), 0.772517 (neg) | |
| data reader: epoch = 0, batch = 309 / 4040 | |
| iter = 309, cls_loss (cur) = 0.540003, cls_loss (avg) = 0.523500, lr = 0.010000 | |
| iter = 309, accuracy (cur) = 0.720000 (all), 0.681818 (pos), 0.750000 (neg) | |
| iter = 309, accuracy (avg) = 0.682308 (all), 0.591013 (pos), 0.772292 (neg) | |
| data reader: epoch = 0, batch = 310 / 4040 | |
| iter = 310, cls_loss (cur) = 0.536902, cls_loss (avg) = 0.523634, lr = 0.010000 | |
| iter = 310, accuracy (cur) = 0.700000 (all), 0.578947 (pos), 0.774194 (neg) | |
| iter = 310, accuracy (avg) = 0.682485 (all), 0.590892 (pos), 0.772311 (neg) | |
| data reader: epoch = 0, batch = 311 / 4040 | |
| iter = 311, cls_loss (cur) = 0.473357, cls_loss (avg) = 0.523131, lr = 0.010000 | |
| iter = 311, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 311, accuracy (avg) = 0.683260 (all), 0.591383 (pos), 0.773388 (neg) | |
| data reader: epoch = 0, batch = 312 / 4040 | |
| iter = 312, cls_loss (cur) = 0.566283, cls_loss (avg) = 0.523563, lr = 0.010000 | |
| iter = 312, accuracy (cur) = 0.760000 (all), 0.650000 (pos), 0.833333 (neg) | |
| iter = 312, accuracy (avg) = 0.684028 (all), 0.591969 (pos), 0.773987 (neg) | |
| data reader: epoch = 0, batch = 313 / 4040 | |
| iter = 313, cls_loss (cur) = 0.467665, cls_loss (avg) = 0.523004, lr = 0.010000 | |
| iter = 313, accuracy (cur) = 0.820000 (all), 0.727273 (pos), 0.892857 (neg) | |
| iter = 313, accuracy (avg) = 0.685387 (all), 0.593322 (pos), 0.775176 (neg) | |
| data reader: epoch = 0, batch = 314 / 4040 | |
| iter = 314, cls_loss (cur) = 0.471623, cls_loss (avg) = 0.522490, lr = 0.010000 | |
| iter = 314, accuracy (cur) = 0.780000 (all), 0.578947 (pos), 0.903226 (neg) | |
| iter = 314, accuracy (avg) = 0.686333 (all), 0.593179 (pos), 0.776456 (neg) | |
| data reader: epoch = 0, batch = 315 / 4040 | |
| iter = 315, cls_loss (cur) = 0.507946, cls_loss (avg) = 0.522344, lr = 0.010000 | |
| iter = 315, accuracy (cur) = 0.700000 (all), 0.450000 (pos), 0.866667 (neg) | |
| iter = 315, accuracy (avg) = 0.686470 (all), 0.591747 (pos), 0.777358 (neg) | |
| data reader: epoch = 0, batch = 316 / 4040 | |
| iter = 316, cls_loss (cur) = 0.517095, cls_loss (avg) = 0.522292, lr = 0.010000 | |
| iter = 316, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 0.954545 (neg) | |
| iter = 316, accuracy (avg) = 0.686605 (all), 0.590829 (pos), 0.779130 (neg) | |
| data reader: epoch = 0, batch = 317 / 4040 | |
| iter = 317, cls_loss (cur) = 0.494547, cls_loss (avg) = 0.522015, lr = 0.010000 | |
| iter = 317, accuracy (cur) = 0.700000 (all), 0.625000 (pos), 0.769231 (neg) | |
| iter = 317, accuracy (avg) = 0.686739 (all), 0.591171 (pos), 0.779031 (neg) | |
| data reader: epoch = 0, batch = 318 / 4040 | |
| iter = 318, cls_loss (cur) = 0.513486, cls_loss (avg) = 0.521929, lr = 0.010000 | |
| iter = 318, accuracy (cur) = 0.740000 (all), 0.636364 (pos), 0.821429 (neg) | |
| iter = 318, accuracy (avg) = 0.687272 (all), 0.591623 (pos), 0.779455 (neg) | |
| data reader: epoch = 0, batch = 319 / 4040 | |
| iter = 319, cls_loss (cur) = 0.506549, cls_loss (avg) = 0.521775, lr = 0.010000 | |
| iter = 319, accuracy (cur) = 0.720000 (all), 0.545455 (pos), 0.857143 (neg) | |
| iter = 319, accuracy (avg) = 0.687599 (all), 0.591161 (pos), 0.780232 (neg) | |
| data reader: epoch = 0, batch = 320 / 4040 | |
| iter = 320, cls_loss (cur) = 0.524675, cls_loss (avg) = 0.521804, lr = 0.010000 | |
| iter = 320, accuracy (cur) = 0.720000 (all), 0.368421 (pos), 0.935484 (neg) | |
| iter = 320, accuracy (avg) = 0.687923 (all), 0.588934 (pos), 0.781785 (neg) | |
| data reader: epoch = 0, batch = 321 / 4040 | |
| iter = 321, cls_loss (cur) = 0.508693, cls_loss (avg) = 0.521673, lr = 0.010000 | |
| iter = 321, accuracy (cur) = 0.740000 (all), 0.680000 (pos), 0.800000 (neg) | |
| iter = 321, accuracy (avg) = 0.688444 (all), 0.589844 (pos), 0.781967 (neg) | |
| data reader: epoch = 0, batch = 322 / 4040 | |
| iter = 322, cls_loss (cur) = 0.496081, cls_loss (avg) = 0.521417, lr = 0.010000 | |
| iter = 322, accuracy (cur) = 0.780000 (all), 0.608696 (pos), 0.925926 (neg) | |
| iter = 322, accuracy (avg) = 0.689360 (all), 0.590033 (pos), 0.783406 (neg) | |
| data reader: epoch = 0, batch = 323 / 4040 | |
| iter = 323, cls_loss (cur) = 0.450931, cls_loss (avg) = 0.520713, lr = 0.010000 | |
| iter = 323, accuracy (cur) = 0.780000 (all), 0.652174 (pos), 0.888889 (neg) | |
| iter = 323, accuracy (avg) = 0.690266 (all), 0.590654 (pos), 0.784461 (neg) | |
| data reader: epoch = 0, batch = 324 / 4040 | |
| iter = 324, cls_loss (cur) = 0.465849, cls_loss (avg) = 0.520164, lr = 0.010000 | |
| iter = 324, accuracy (cur) = 0.700000 (all), 0.562500 (pos), 0.944444 (neg) | |
| iter = 324, accuracy (avg) = 0.690363 (all), 0.590373 (pos), 0.786061 (neg) | |
| data reader: epoch = 0, batch = 325 / 4040 | |
| iter = 325, cls_loss (cur) = 0.580187, cls_loss (avg) = 0.520764, lr = 0.010000 | |
| iter = 325, accuracy (cur) = 0.720000 (all), 0.840000 (pos), 0.600000 (neg) | |
| iter = 325, accuracy (avg) = 0.690660 (all), 0.592869 (pos), 0.784200 (neg) | |
| data reader: epoch = 0, batch = 326 / 4040 | |
| iter = 326, cls_loss (cur) = 0.435446, cls_loss (avg) = 0.519911, lr = 0.010000 | |
| iter = 326, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.888889 (neg) | |
| iter = 326, accuracy (avg) = 0.691753 (all), 0.594440 (pos), 0.785247 (neg) | |
| data reader: epoch = 0, batch = 327 / 4040 | |
| iter = 327, cls_loss (cur) = 0.457888, cls_loss (avg) = 0.519291, lr = 0.010000 | |
| iter = 327, accuracy (cur) = 0.760000 (all), 0.774194 (pos), 0.736842 (neg) | |
| iter = 327, accuracy (avg) = 0.692436 (all), 0.596238 (pos), 0.784763 (neg) | |
| data reader: epoch = 0, batch = 328 / 4040 | |
| iter = 328, cls_loss (cur) = 0.532543, cls_loss (avg) = 0.519423, lr = 0.010000 | |
| iter = 328, accuracy (cur) = 0.640000 (all), 0.733333 (pos), 0.500000 (neg) | |
| iter = 328, accuracy (avg) = 0.691911 (all), 0.597609 (pos), 0.781916 (neg) | |
| data reader: epoch = 0, batch = 329 / 4040 | |
| iter = 329, cls_loss (cur) = 0.541882, cls_loss (avg) = 0.519648, lr = 0.010000 | |
| iter = 329, accuracy (cur) = 0.800000 (all), 0.869565 (pos), 0.740741 (neg) | |
| iter = 329, accuracy (avg) = 0.692992 (all), 0.600328 (pos), 0.781504 (neg) | |
| data reader: epoch = 0, batch = 330 / 4040 | |
| iter = 330, cls_loss (cur) = 0.405152, cls_loss (avg) = 0.518503, lr = 0.010000 | |
| iter = 330, accuracy (cur) = 0.820000 (all), 0.826087 (pos), 0.814815 (neg) | |
| iter = 330, accuracy (avg) = 0.694262 (all), 0.602586 (pos), 0.781837 (neg) | |
| data reader: epoch = 0, batch = 331 / 4040 | |
| iter = 331, cls_loss (cur) = 0.462769, cls_loss (avg) = 0.517946, lr = 0.010000 | |
| iter = 331, accuracy (cur) = 0.780000 (all), 0.629630 (pos), 0.956522 (neg) | |
| iter = 331, accuracy (avg) = 0.695120 (all), 0.602857 (pos), 0.783584 (neg) | |
| data reader: epoch = 0, batch = 332 / 4040 | |
| iter = 332, cls_loss (cur) = 0.542583, cls_loss (avg) = 0.518192, lr = 0.010000 | |
| iter = 332, accuracy (cur) = 0.700000 (all), 0.566667 (pos), 0.900000 (neg) | |
| iter = 332, accuracy (avg) = 0.695168 (all), 0.602495 (pos), 0.784748 (neg) | |
| data reader: epoch = 0, batch = 333 / 4040 | |
| iter = 333, cls_loss (cur) = 0.567378, cls_loss (avg) = 0.518684, lr = 0.010000 | |
| iter = 333, accuracy (cur) = 0.620000 (all), 0.620690 (pos), 0.619048 (neg) | |
| iter = 333, accuracy (avg) = 0.694417 (all), 0.602677 (pos), 0.783091 (neg) | |
| data reader: epoch = 0, batch = 334 / 4040 | |
| iter = 334, cls_loss (cur) = 0.608595, cls_loss (avg) = 0.519583, lr = 0.010000 | |
| iter = 334, accuracy (cur) = 0.640000 (all), 0.535714 (pos), 0.772727 (neg) | |
| iter = 334, accuracy (avg) = 0.693873 (all), 0.602007 (pos), 0.782987 (neg) | |
| data reader: epoch = 0, batch = 335 / 4040 | |
| iter = 335, cls_loss (cur) = 0.549197, cls_loss (avg) = 0.519879, lr = 0.010000 | |
| iter = 335, accuracy (cur) = 0.720000 (all), 0.764706 (pos), 0.696970 (neg) | |
| iter = 335, accuracy (avg) = 0.694134 (all), 0.603634 (pos), 0.782127 (neg) | |
| data reader: epoch = 0, batch = 336 / 4040 | |
| iter = 336, cls_loss (cur) = 0.550219, cls_loss (avg) = 0.520182, lr = 0.010000 | |
| iter = 336, accuracy (cur) = 0.680000 (all), 0.615385 (pos), 0.750000 (neg) | |
| iter = 336, accuracy (avg) = 0.693992 (all), 0.603751 (pos), 0.781806 (neg) | |
| data reader: epoch = 0, batch = 337 / 4040 | |
| iter = 337, cls_loss (cur) = 0.492146, cls_loss (avg) = 0.519902, lr = 0.010000 | |
| iter = 337, accuracy (cur) = 0.820000 (all), 0.714286 (pos), 0.896552 (neg) | |
| iter = 337, accuracy (avg) = 0.695253 (all), 0.604857 (pos), 0.782953 (neg) | |
| data reader: epoch = 0, batch = 338 / 4040 | |
| iter = 338, cls_loss (cur) = 0.531186, cls_loss (avg) = 0.520015, lr = 0.010000 | |
| iter = 338, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 0.857143 (neg) | |
| iter = 338, accuracy (avg) = 0.695300 (all), 0.603808 (pos), 0.783695 (neg) | |
| data reader: epoch = 0, batch = 339 / 4040 | |
| iter = 339, cls_loss (cur) = 0.474594, cls_loss (avg) = 0.519561, lr = 0.010000 | |
| iter = 339, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.862069 (neg) | |
| iter = 339, accuracy (avg) = 0.696147 (all), 0.604437 (pos), 0.784479 (neg) | |
| data reader: epoch = 0, batch = 340 / 4040 | |
| iter = 340, cls_loss (cur) = 0.499227, cls_loss (avg) = 0.519357, lr = 0.010000 | |
| iter = 340, accuracy (cur) = 0.680000 (all), 0.464286 (pos), 0.954545 (neg) | |
| iter = 340, accuracy (avg) = 0.695986 (all), 0.603035 (pos), 0.786180 (neg) | |
| data reader: epoch = 0, batch = 341 / 4040 | |
| iter = 341, cls_loss (cur) = 0.543250, cls_loss (avg) = 0.519596, lr = 0.010000 | |
| iter = 341, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 1.000000 (neg) | |
| iter = 341, accuracy (avg) = 0.696026 (all), 0.602005 (pos), 0.788318 (neg) | |
| data reader: epoch = 0, batch = 342 / 4040 | |
| iter = 342, cls_loss (cur) = 0.435509, cls_loss (avg) = 0.518755, lr = 0.010000 | |
| iter = 342, accuracy (cur) = 0.840000 (all), 0.700000 (pos), 0.933333 (neg) | |
| iter = 342, accuracy (avg) = 0.697465 (all), 0.602985 (pos), 0.789768 (neg) | |
| data reader: epoch = 0, batch = 343 / 4040 | |
| iter = 343, cls_loss (cur) = 0.493019, cls_loss (avg) = 0.518498, lr = 0.010000 | |
| iter = 343, accuracy (cur) = 0.740000 (all), 0.782609 (pos), 0.703704 (neg) | |
| iter = 343, accuracy (avg) = 0.697891 (all), 0.604781 (pos), 0.788907 (neg) | |
| data reader: epoch = 0, batch = 344 / 4040 | |
| iter = 344, cls_loss (cur) = 0.473528, cls_loss (avg) = 0.518048, lr = 0.010000 | |
| iter = 344, accuracy (cur) = 0.720000 (all), 0.593750 (pos), 0.944444 (neg) | |
| iter = 344, accuracy (avg) = 0.698112 (all), 0.604671 (pos), 0.790463 (neg) | |
| data reader: epoch = 0, batch = 345 / 4040 | |
| iter = 345, cls_loss (cur) = 0.520256, cls_loss (avg) = 0.518070, lr = 0.010000 | |
| iter = 345, accuracy (cur) = 0.640000 (all), 0.687500 (pos), 0.555556 (neg) | |
| iter = 345, accuracy (avg) = 0.697531 (all), 0.605499 (pos), 0.788114 (neg) | |
| data reader: epoch = 0, batch = 346 / 4040 | |
| iter = 346, cls_loss (cur) = 0.666198, cls_loss (avg) = 0.519552, lr = 0.010000 | |
| iter = 346, accuracy (cur) = 0.620000 (all), 0.652174 (pos), 0.592593 (neg) | |
| iter = 346, accuracy (avg) = 0.696755 (all), 0.605966 (pos), 0.786158 (neg) | |
| data reader: epoch = 0, batch = 347 / 4040 | |
| iter = 347, cls_loss (cur) = 0.549086, cls_loss (avg) = 0.519847, lr = 0.010000 | |
| iter = 347, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 347, accuracy (avg) = 0.697588 (all), 0.607684 (pos), 0.786123 (neg) | |
| data reader: epoch = 0, batch = 348 / 4040 | |
| iter = 348, cls_loss (cur) = 0.549173, cls_loss (avg) = 0.520140, lr = 0.010000 | |
| iter = 348, accuracy (cur) = 0.740000 (all), 0.851852 (pos), 0.608696 (neg) | |
| iter = 348, accuracy (avg) = 0.698012 (all), 0.610126 (pos), 0.784349 (neg) | |
| data reader: epoch = 0, batch = 349 / 4040 | |
| iter = 349, cls_loss (cur) = 0.533026, cls_loss (avg) = 0.520269, lr = 0.010000 | |
| iter = 349, accuracy (cur) = 0.680000 (all), 0.555556 (pos), 0.826087 (neg) | |
| iter = 349, accuracy (avg) = 0.697832 (all), 0.609580 (pos), 0.784766 (neg) | |
| data reader: epoch = 0, batch = 350 / 4040 | |
| iter = 350, cls_loss (cur) = 0.475065, cls_loss (avg) = 0.519817, lr = 0.010000 | |
| iter = 350, accuracy (cur) = 0.800000 (all), 0.769231 (pos), 0.833333 (neg) | |
| iter = 350, accuracy (avg) = 0.698854 (all), 0.611176 (pos), 0.785252 (neg) | |
| data reader: epoch = 0, batch = 351 / 4040 | |
| iter = 351, cls_loss (cur) = 0.557974, cls_loss (avg) = 0.520199, lr = 0.010000 | |
| iter = 351, accuracy (cur) = 0.760000 (all), 0.821429 (pos), 0.681818 (neg) | |
| iter = 351, accuracy (avg) = 0.699465 (all), 0.613279 (pos), 0.784217 (neg) | |
| data reader: epoch = 0, batch = 352 / 4040 | |
| iter = 352, cls_loss (cur) = 0.546160, cls_loss (avg) = 0.520458, lr = 0.010000 | |
| iter = 352, accuracy (cur) = 0.680000 (all), 0.583333 (pos), 0.769231 (neg) | |
| iter = 352, accuracy (avg) = 0.699270 (all), 0.612980 (pos), 0.784067 (neg) | |
| data reader: epoch = 0, batch = 353 / 4040 | |
| iter = 353, cls_loss (cur) = 0.531793, cls_loss (avg) = 0.520572, lr = 0.010000 | |
| iter = 353, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.714286 (neg) | |
| iter = 353, accuracy (avg) = 0.699878 (all), 0.615032 (pos), 0.783370 (neg) | |
| data reader: epoch = 0, batch = 354 / 4040 | |
| iter = 354, cls_loss (cur) = 0.463661, cls_loss (avg) = 0.520003, lr = 0.010000 | |
| iter = 354, accuracy (cur) = 0.900000 (all), 0.827586 (pos), 1.000000 (neg) | |
| iter = 354, accuracy (avg) = 0.701879 (all), 0.617157 (pos), 0.785536 (neg) | |
| data reader: epoch = 0, batch = 355 / 4040 | |
| iter = 355, cls_loss (cur) = 0.533634, cls_loss (avg) = 0.520139, lr = 0.010000 | |
| iter = 355, accuracy (cur) = 0.700000 (all), 0.703704 (pos), 0.695652 (neg) | |
| iter = 355, accuracy (avg) = 0.701860 (all), 0.618023 (pos), 0.784637 (neg) | |
| data reader: epoch = 0, batch = 356 / 4040 | |
| iter = 356, cls_loss (cur) = 0.523255, cls_loss (avg) = 0.520170, lr = 0.010000 | |
| iter = 356, accuracy (cur) = 0.740000 (all), 0.724138 (pos), 0.761905 (neg) | |
| iter = 356, accuracy (avg) = 0.702242 (all), 0.619084 (pos), 0.784410 (neg) | |
| data reader: epoch = 0, batch = 357 / 4040 | |
| iter = 357, cls_loss (cur) = 0.490304, cls_loss (avg) = 0.519871, lr = 0.010000 | |
| iter = 357, accuracy (cur) = 0.760000 (all), 0.857143 (pos), 0.636364 (neg) | |
| iter = 357, accuracy (avg) = 0.702819 (all), 0.621464 (pos), 0.782929 (neg) | |
| data reader: epoch = 0, batch = 358 / 4040 | |
| iter = 358, cls_loss (cur) = 0.518082, cls_loss (avg) = 0.519853, lr = 0.010000 | |
| iter = 358, accuracy (cur) = 0.760000 (all), 0.814815 (pos), 0.695652 (neg) | |
| iter = 358, accuracy (avg) = 0.703391 (all), 0.623398 (pos), 0.782057 (neg) | |
| data reader: epoch = 0, batch = 359 / 4040 | |
| iter = 359, cls_loss (cur) = 0.548611, cls_loss (avg) = 0.520141, lr = 0.010000 | |
| iter = 359, accuracy (cur) = 0.740000 (all), 0.882353 (pos), 0.666667 (neg) | |
| iter = 359, accuracy (avg) = 0.703757 (all), 0.625987 (pos), 0.780903 (neg) | |
| data reader: epoch = 0, batch = 360 / 4040 | |
| iter = 360, cls_loss (cur) = 0.518449, cls_loss (avg) = 0.520124, lr = 0.010000 | |
| iter = 360, accuracy (cur) = 0.700000 (all), 0.620690 (pos), 0.809524 (neg) | |
| iter = 360, accuracy (avg) = 0.703719 (all), 0.625934 (pos), 0.781189 (neg) | |
| data reader: epoch = 0, batch = 361 / 4040 | |
| iter = 361, cls_loss (cur) = 0.504467, cls_loss (avg) = 0.519968, lr = 0.010000 | |
| iter = 361, accuracy (cur) = 0.780000 (all), 0.700000 (pos), 0.833333 (neg) | |
| iter = 361, accuracy (avg) = 0.704482 (all), 0.626675 (pos), 0.781710 (neg) | |
| data reader: epoch = 0, batch = 362 / 4040 | |
| iter = 362, cls_loss (cur) = 0.518720, cls_loss (avg) = 0.519955, lr = 0.010000 | |
| iter = 362, accuracy (cur) = 0.780000 (all), 0.652174 (pos), 0.888889 (neg) | |
| iter = 362, accuracy (avg) = 0.705237 (all), 0.626930 (pos), 0.782782 (neg) | |
| data reader: epoch = 0, batch = 363 / 4040 | |
| iter = 363, cls_loss (cur) = 0.487845, cls_loss (avg) = 0.519634, lr = 0.010000 | |
| iter = 363, accuracy (cur) = 0.780000 (all), 0.608696 (pos), 0.925926 (neg) | |
| iter = 363, accuracy (avg) = 0.705985 (all), 0.626748 (pos), 0.784214 (neg) | |
| data reader: epoch = 0, batch = 364 / 4040 | |
| iter = 364, cls_loss (cur) = 0.450044, cls_loss (avg) = 0.518938, lr = 0.010000 | |
| iter = 364, accuracy (cur) = 0.800000 (all), 0.619048 (pos), 0.931034 (neg) | |
| iter = 364, accuracy (avg) = 0.706925 (all), 0.626671 (pos), 0.785682 (neg) | |
| data reader: epoch = 0, batch = 365 / 4040 | |
| iter = 365, cls_loss (cur) = 0.632469, cls_loss (avg) = 0.520073, lr = 0.010000 | |
| iter = 365, accuracy (cur) = 0.640000 (all), 0.483871 (pos), 0.894737 (neg) | |
| iter = 365, accuracy (avg) = 0.706256 (all), 0.625243 (pos), 0.786772 (neg) | |
| data reader: epoch = 0, batch = 366 / 4040 | |
| iter = 366, cls_loss (cur) = 0.425338, cls_loss (avg) = 0.519126, lr = 0.010000 | |
| iter = 366, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 366, accuracy (avg) = 0.706793 (all), 0.626027 (pos), 0.787165 (neg) | |
| data reader: epoch = 0, batch = 367 / 4040 | |
| iter = 367, cls_loss (cur) = 0.575139, cls_loss (avg) = 0.519686, lr = 0.010000 | |
| iter = 367, accuracy (cur) = 0.700000 (all), 0.470588 (pos), 0.818182 (neg) | |
| iter = 367, accuracy (avg) = 0.706725 (all), 0.624473 (pos), 0.787476 (neg) | |
| data reader: epoch = 0, batch = 368 / 4040 | |
| iter = 368, cls_loss (cur) = 0.433746, cls_loss (avg) = 0.518827, lr = 0.010000 | |
| iter = 368, accuracy (cur) = 0.820000 (all), 0.720000 (pos), 0.920000 (neg) | |
| iter = 368, accuracy (avg) = 0.707858 (all), 0.625428 (pos), 0.788801 (neg) | |
| data reader: epoch = 0, batch = 369 / 4040 | |
| iter = 369, cls_loss (cur) = 0.417321, cls_loss (avg) = 0.517812, lr = 0.010000 | |
| iter = 369, accuracy (cur) = 0.860000 (all), 0.818182 (pos), 0.892857 (neg) | |
| iter = 369, accuracy (avg) = 0.709380 (all), 0.627356 (pos), 0.789841 (neg) | |
| data reader: epoch = 0, batch = 370 / 4040 | |
| iter = 370, cls_loss (cur) = 0.571657, cls_loss (avg) = 0.518350, lr = 0.010000 | |
| iter = 370, accuracy (cur) = 0.640000 (all), 0.461538 (pos), 0.833333 (neg) | |
| iter = 370, accuracy (avg) = 0.708686 (all), 0.625698 (pos), 0.790276 (neg) | |
| data reader: epoch = 0, batch = 371 / 4040 | |
| iter = 371, cls_loss (cur) = 0.501054, cls_loss (avg) = 0.518177, lr = 0.010000 | |
| iter = 371, accuracy (cur) = 0.740000 (all), 0.640000 (pos), 0.840000 (neg) | |
| iter = 371, accuracy (avg) = 0.708999 (all), 0.625841 (pos), 0.790774 (neg) | |
| data reader: epoch = 0, batch = 372 / 4040 | |
| iter = 372, cls_loss (cur) = 0.512806, cls_loss (avg) = 0.518123, lr = 0.010000 | |
| iter = 372, accuracy (cur) = 0.760000 (all), 0.680000 (pos), 0.840000 (neg) | |
| iter = 372, accuracy (avg) = 0.709509 (all), 0.626382 (pos), 0.791266 (neg) | |
| data reader: epoch = 0, batch = 373 / 4040 | |
| iter = 373, cls_loss (cur) = 0.586790, cls_loss (avg) = 0.518810, lr = 0.010000 | |
| iter = 373, accuracy (cur) = 0.660000 (all), 0.541667 (pos), 0.769231 (neg) | |
| iter = 373, accuracy (avg) = 0.709014 (all), 0.625535 (pos), 0.791046 (neg) | |
| data reader: epoch = 0, batch = 374 / 4040 | |
| iter = 374, cls_loss (cur) = 0.449781, cls_loss (avg) = 0.518120, lr = 0.010000 | |
| iter = 374, accuracy (cur) = 0.780000 (all), 0.718750 (pos), 0.888889 (neg) | |
| iter = 374, accuracy (avg) = 0.709724 (all), 0.626467 (pos), 0.792024 (neg) | |
| data reader: epoch = 0, batch = 375 / 4040 | |
| iter = 375, cls_loss (cur) = 0.419205, cls_loss (avg) = 0.517131, lr = 0.010000 | |
| iter = 375, accuracy (cur) = 0.800000 (all), 0.862069 (pos), 0.714286 (neg) | |
| iter = 375, accuracy (avg) = 0.710626 (all), 0.628823 (pos), 0.791247 (neg) | |
| data reader: epoch = 0, batch = 376 / 4040 | |
| iter = 376, cls_loss (cur) = 0.523789, cls_loss (avg) = 0.517197, lr = 0.010000 | |
| iter = 376, accuracy (cur) = 0.760000 (all), 0.833333 (pos), 0.692308 (neg) | |
| iter = 376, accuracy (avg) = 0.711120 (all), 0.630868 (pos), 0.790257 (neg) | |
| data reader: epoch = 0, batch = 377 / 4040 | |
| iter = 377, cls_loss (cur) = 0.534557, cls_loss (avg) = 0.517371, lr = 0.010000 | |
| iter = 377, accuracy (cur) = 0.700000 (all), 0.774194 (pos), 0.578947 (neg) | |
| iter = 377, accuracy (avg) = 0.711009 (all), 0.632302 (pos), 0.788144 (neg) | |
| data reader: epoch = 0, batch = 378 / 4040 | |
| iter = 378, cls_loss (cur) = 0.470403, cls_loss (avg) = 0.516901, lr = 0.010000 | |
| iter = 378, accuracy (cur) = 0.820000 (all), 0.923077 (pos), 0.708333 (neg) | |
| iter = 378, accuracy (avg) = 0.712099 (all), 0.635209 (pos), 0.787346 (neg) | |
| data reader: epoch = 0, batch = 379 / 4040 | |
| iter = 379, cls_loss (cur) = 0.529931, cls_loss (avg) = 0.517031, lr = 0.010000 | |
| iter = 379, accuracy (cur) = 0.760000 (all), 0.653846 (pos), 0.875000 (neg) | |
| iter = 379, accuracy (avg) = 0.712578 (all), 0.635396 (pos), 0.788223 (neg) | |
| data reader: epoch = 0, batch = 380 / 4040 | |
| iter = 380, cls_loss (cur) = 0.488273, cls_loss (avg) = 0.516744, lr = 0.010000 | |
| iter = 380, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.760000 (neg) | |
| iter = 380, accuracy (avg) = 0.713252 (all), 0.637042 (pos), 0.787940 (neg) | |
| data reader: epoch = 0, batch = 381 / 4040 | |
| iter = 381, cls_loss (cur) = 0.457492, cls_loss (avg) = 0.516151, lr = 0.010000 | |
| iter = 381, accuracy (cur) = 0.800000 (all), 0.730769 (pos), 0.875000 (neg) | |
| iter = 381, accuracy (avg) = 0.714120 (all), 0.637979 (pos), 0.788811 (neg) | |
| data reader: epoch = 0, batch = 382 / 4040 | |
| iter = 382, cls_loss (cur) = 0.495361, cls_loss (avg) = 0.515943, lr = 0.010000 | |
| iter = 382, accuracy (cur) = 0.780000 (all), 0.818182 (pos), 0.750000 (neg) | |
| iter = 382, accuracy (avg) = 0.714778 (all), 0.639781 (pos), 0.788423 (neg) | |
| data reader: epoch = 0, batch = 383 / 4040 | |
| iter = 383, cls_loss (cur) = 0.499993, cls_loss (avg) = 0.515784, lr = 0.010000 | |
| iter = 383, accuracy (cur) = 0.760000 (all), 0.750000 (pos), 0.769231 (neg) | |
| iter = 383, accuracy (avg) = 0.715231 (all), 0.640883 (pos), 0.788231 (neg) | |
| data reader: epoch = 0, batch = 384 / 4040 | |
| iter = 384, cls_loss (cur) = 0.581302, cls_loss (avg) = 0.516439, lr = 0.010000 | |
| iter = 384, accuracy (cur) = 0.640000 (all), 0.440000 (pos), 0.840000 (neg) | |
| iter = 384, accuracy (avg) = 0.714478 (all), 0.638874 (pos), 0.788749 (neg) | |
| data reader: epoch = 0, batch = 385 / 4040 | |
| iter = 385, cls_loss (cur) = 0.424510, cls_loss (avg) = 0.515520, lr = 0.010000 | |
| iter = 385, accuracy (cur) = 0.800000 (all), 0.714286 (pos), 0.909091 (neg) | |
| iter = 385, accuracy (avg) = 0.715334 (all), 0.639628 (pos), 0.789952 (neg) | |
| data reader: epoch = 0, batch = 386 / 4040 | |
| iter = 386, cls_loss (cur) = 0.430076, cls_loss (avg) = 0.514665, lr = 0.010000 | |
| iter = 386, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 386, accuracy (avg) = 0.716380 (all), 0.641149 (pos), 0.790514 (neg) | |
| data reader: epoch = 0, batch = 387 / 4040 | |
| iter = 387, cls_loss (cur) = 0.436413, cls_loss (avg) = 0.513883, lr = 0.010000 | |
| iter = 387, accuracy (cur) = 0.760000 (all), 0.777778 (pos), 0.739130 (neg) | |
| iter = 387, accuracy (avg) = 0.716816 (all), 0.642515 (pos), 0.790000 (neg) | |
| data reader: epoch = 0, batch = 388 / 4040 | |
| iter = 388, cls_loss (cur) = 0.500587, cls_loss (avg) = 0.513750, lr = 0.010000 | |
| iter = 388, accuracy (cur) = 0.720000 (all), 0.571429 (pos), 0.909091 (neg) | |
| iter = 388, accuracy (avg) = 0.716848 (all), 0.641804 (pos), 0.791191 (neg) | |
| data reader: epoch = 0, batch = 389 / 4040 | |
| iter = 389, cls_loss (cur) = 0.532439, cls_loss (avg) = 0.513937, lr = 0.010000 | |
| iter = 389, accuracy (cur) = 0.780000 (all), 0.833333 (pos), 0.730769 (neg) | |
| iter = 389, accuracy (avg) = 0.717480 (all), 0.643720 (pos), 0.790587 (neg) | |
| data reader: epoch = 0, batch = 390 / 4040 | |
| iter = 390, cls_loss (cur) = 0.373709, cls_loss (avg) = 0.512535, lr = 0.010000 | |
| iter = 390, accuracy (cur) = 0.880000 (all), 0.900000 (pos), 0.866667 (neg) | |
| iter = 390, accuracy (avg) = 0.719105 (all), 0.646282 (pos), 0.791348 (neg) | |
| data reader: epoch = 0, batch = 391 / 4040 | |
| iter = 391, cls_loss (cur) = 0.463411, cls_loss (avg) = 0.512043, lr = 0.010000 | |
| iter = 391, accuracy (cur) = 0.800000 (all), 0.714286 (pos), 0.909091 (neg) | |
| iter = 391, accuracy (avg) = 0.719914 (all), 0.646962 (pos), 0.792525 (neg) | |
| data reader: epoch = 0, batch = 392 / 4040 | |
| iter = 392, cls_loss (cur) = 0.633919, cls_loss (avg) = 0.513262, lr = 0.010000 | |
| iter = 392, accuracy (cur) = 0.580000 (all), 0.476190 (pos), 0.655172 (neg) | |
| iter = 392, accuracy (avg) = 0.718515 (all), 0.645255 (pos), 0.791152 (neg) | |
| data reader: epoch = 0, batch = 393 / 4040 | |
| iter = 393, cls_loss (cur) = 0.468928, cls_loss (avg) = 0.512819, lr = 0.010000 | |
| iter = 393, accuracy (cur) = 0.800000 (all), 0.652174 (pos), 0.925926 (neg) | |
| iter = 393, accuracy (avg) = 0.719330 (all), 0.645324 (pos), 0.792499 (neg) | |
| data reader: epoch = 0, batch = 394 / 4040 | |
| iter = 394, cls_loss (cur) = 0.491141, cls_loss (avg) = 0.512602, lr = 0.010000 | |
| iter = 394, accuracy (cur) = 0.800000 (all), 0.791667 (pos), 0.807692 (neg) | |
| iter = 394, accuracy (avg) = 0.720136 (all), 0.646787 (pos), 0.792651 (neg) | |
| data reader: epoch = 0, batch = 395 / 4040 | |
| iter = 395, cls_loss (cur) = 0.469975, cls_loss (avg) = 0.512176, lr = 0.010000 | |
| iter = 395, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.800000 (neg) | |
| iter = 395, accuracy (avg) = 0.721135 (all), 0.648653 (pos), 0.792725 (neg) | |
| data reader: epoch = 0, batch = 396 / 4040 | |
| iter = 396, cls_loss (cur) = 0.493781, cls_loss (avg) = 0.511992, lr = 0.010000 | |
| iter = 396, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.884615 (neg) | |
| iter = 396, accuracy (avg) = 0.721724 (all), 0.648833 (pos), 0.793644 (neg) | |
| data reader: epoch = 0, batch = 397 / 4040 | |
| iter = 397, cls_loss (cur) = 0.403394, cls_loss (avg) = 0.510906, lr = 0.010000 | |
| iter = 397, accuracy (cur) = 0.900000 (all), 0.800000 (pos), 0.966667 (neg) | |
| iter = 397, accuracy (avg) = 0.723506 (all), 0.650345 (pos), 0.795374 (neg) | |
| data reader: epoch = 0, batch = 398 / 4040 | |
| iter = 398, cls_loss (cur) = 0.463547, cls_loss (avg) = 0.510432, lr = 0.010000 | |
| iter = 398, accuracy (cur) = 0.780000 (all), 0.772727 (pos), 0.785714 (neg) | |
| iter = 398, accuracy (avg) = 0.724071 (all), 0.651568 (pos), 0.795277 (neg) | |
| data reader: epoch = 0, batch = 399 / 4040 | |
| iter = 399, cls_loss (cur) = 0.462134, cls_loss (avg) = 0.509949, lr = 0.010000 | |
| iter = 399, accuracy (cur) = 0.800000 (all), 0.666667 (pos), 0.956522 (neg) | |
| iter = 399, accuracy (avg) = 0.724831 (all), 0.651719 (pos), 0.796890 (neg) | |
| data reader: epoch = 0, batch = 400 / 4040 | |
| iter = 400, cls_loss (cur) = 0.511277, cls_loss (avg) = 0.509962, lr = 0.010000 | |
| iter = 400, accuracy (cur) = 0.780000 (all), 0.642857 (pos), 0.954545 (neg) | |
| iter = 400, accuracy (avg) = 0.725382 (all), 0.651631 (pos), 0.798466 (neg) | |
| data reader: epoch = 0, batch = 401 / 4040 | |
| iter = 401, cls_loss (cur) = 0.390425, cls_loss (avg) = 0.508767, lr = 0.010000 | |
| iter = 401, accuracy (cur) = 0.880000 (all), 0.850000 (pos), 0.900000 (neg) | |
| iter = 401, accuracy (avg) = 0.726929 (all), 0.653614 (pos), 0.799482 (neg) | |
| data reader: epoch = 0, batch = 402 / 4040 | |
| iter = 402, cls_loss (cur) = 0.378445, cls_loss (avg) = 0.507464, lr = 0.010000 | |
| iter = 402, accuracy (cur) = 0.840000 (all), 0.772727 (pos), 0.892857 (neg) | |
| iter = 402, accuracy (avg) = 0.728059 (all), 0.654806 (pos), 0.800415 (neg) | |
| data reader: epoch = 0, batch = 403 / 4040 | |
| iter = 403, cls_loss (cur) = 0.463337, cls_loss (avg) = 0.507023, lr = 0.010000 | |
| iter = 403, accuracy (cur) = 0.780000 (all), 0.740741 (pos), 0.826087 (neg) | |
| iter = 403, accuracy (avg) = 0.728579 (all), 0.655665 (pos), 0.800672 (neg) | |
| data reader: epoch = 0, batch = 404 / 4040 | |
| iter = 404, cls_loss (cur) = 0.455724, cls_loss (avg) = 0.506510, lr = 0.010000 | |
| iter = 404, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 404, accuracy (avg) = 0.728893 (all), 0.656145 (pos), 0.800926 (neg) | |
| data reader: epoch = 0, batch = 405 / 4040 | |
| iter = 405, cls_loss (cur) = 0.386195, cls_loss (avg) = 0.505306, lr = 0.010000 | |
| iter = 405, accuracy (cur) = 0.840000 (all), 0.888889 (pos), 0.812500 (neg) | |
| iter = 405, accuracy (avg) = 0.730004 (all), 0.658473 (pos), 0.801042 (neg) | |
| data reader: epoch = 0, batch = 406 / 4040 | |
| iter = 406, cls_loss (cur) = 0.477295, cls_loss (avg) = 0.505026, lr = 0.010000 | |
| iter = 406, accuracy (cur) = 0.760000 (all), 0.678571 (pos), 0.863636 (neg) | |
| iter = 406, accuracy (avg) = 0.730304 (all), 0.658674 (pos), 0.801668 (neg) | |
| data reader: epoch = 0, batch = 407 / 4040 | |
| iter = 407, cls_loss (cur) = 0.576699, cls_loss (avg) = 0.505743, lr = 0.010000 | |
| iter = 407, accuracy (cur) = 0.680000 (all), 0.826087 (pos), 0.555556 (neg) | |
| iter = 407, accuracy (avg) = 0.729801 (all), 0.660348 (pos), 0.799207 (neg) | |
| data reader: epoch = 0, batch = 408 / 4040 | |
| iter = 408, cls_loss (cur) = 0.515606, cls_loss (avg) = 0.505842, lr = 0.010000 | |
| iter = 408, accuracy (cur) = 0.700000 (all), 0.615385 (pos), 0.791667 (neg) | |
| iter = 408, accuracy (avg) = 0.729503 (all), 0.659898 (pos), 0.799131 (neg) | |
| data reader: epoch = 0, batch = 409 / 4040 | |
| iter = 409, cls_loss (cur) = 0.538814, cls_loss (avg) = 0.506171, lr = 0.010000 | |
| iter = 409, accuracy (cur) = 0.680000 (all), 0.612903 (pos), 0.789474 (neg) | |
| iter = 409, accuracy (avg) = 0.729008 (all), 0.659428 (pos), 0.799035 (neg) | |
| data reader: epoch = 0, batch = 410 / 4040 | |
| iter = 410, cls_loss (cur) = 0.491174, cls_loss (avg) = 0.506021, lr = 0.010000 | |
| iter = 410, accuracy (cur) = 0.800000 (all), 0.896552 (pos), 0.666667 (neg) | |
| iter = 410, accuracy (avg) = 0.729718 (all), 0.661800 (pos), 0.797711 (neg) | |
| data reader: epoch = 0, batch = 411 / 4040 | |
| iter = 411, cls_loss (cur) = 0.442551, cls_loss (avg) = 0.505387, lr = 0.010000 | |
| iter = 411, accuracy (cur) = 0.860000 (all), 0.931034 (pos), 0.761905 (neg) | |
| iter = 411, accuracy (avg) = 0.731021 (all), 0.664492 (pos), 0.797353 (neg) | |
| data reader: epoch = 0, batch = 412 / 4040 | |
| iter = 412, cls_loss (cur) = 0.488337, cls_loss (avg) = 0.505216, lr = 0.010000 | |
| iter = 412, accuracy (cur) = 0.780000 (all), 0.954545 (pos), 0.642857 (neg) | |
| iter = 412, accuracy (avg) = 0.731510 (all), 0.667392 (pos), 0.795808 (neg) | |
| data reader: epoch = 0, batch = 413 / 4040 | |
| iter = 413, cls_loss (cur) = 0.540794, cls_loss (avg) = 0.505572, lr = 0.010000 | |
| iter = 413, accuracy (cur) = 0.820000 (all), 0.916667 (pos), 0.730769 (neg) | |
| iter = 413, accuracy (avg) = 0.732395 (all), 0.669885 (pos), 0.795158 (neg) | |
| data reader: epoch = 0, batch = 414 / 4040 | |
| iter = 414, cls_loss (cur) = 0.370181, cls_loss (avg) = 0.504218, lr = 0.010000 | |
| iter = 414, accuracy (cur) = 0.820000 (all), 0.758621 (pos), 0.904762 (neg) | |
| iter = 414, accuracy (avg) = 0.733271 (all), 0.670773 (pos), 0.796254 (neg) | |
| data reader: epoch = 0, batch = 415 / 4040 | |
| iter = 415, cls_loss (cur) = 0.492482, cls_loss (avg) = 0.504101, lr = 0.010000 | |
| iter = 415, accuracy (cur) = 0.700000 (all), 0.678571 (pos), 0.727273 (neg) | |
| iter = 415, accuracy (avg) = 0.732939 (all), 0.670851 (pos), 0.795564 (neg) | |
| data reader: epoch = 0, batch = 416 / 4040 | |
| iter = 416, cls_loss (cur) = 0.527290, cls_loss (avg) = 0.504333, lr = 0.010000 | |
| iter = 416, accuracy (cur) = 0.760000 (all), 0.793103 (pos), 0.714286 (neg) | |
| iter = 416, accuracy (avg) = 0.733209 (all), 0.672073 (pos), 0.794751 (neg) | |
| data reader: epoch = 0, batch = 417 / 4040 | |
| iter = 417, cls_loss (cur) = 0.480625, cls_loss (avg) = 0.504096, lr = 0.010000 | |
| iter = 417, accuracy (cur) = 0.800000 (all), 0.692308 (pos), 0.916667 (neg) | |
| iter = 417, accuracy (avg) = 0.733877 (all), 0.672275 (pos), 0.795970 (neg) | |
| data reader: epoch = 0, batch = 418 / 4040 | |
| iter = 418, cls_loss (cur) = 0.490114, cls_loss (avg) = 0.503956, lr = 0.010000 | |
| iter = 418, accuracy (cur) = 0.820000 (all), 0.884615 (pos), 0.750000 (neg) | |
| iter = 418, accuracy (avg) = 0.734738 (all), 0.674399 (pos), 0.795511 (neg) | |
| data reader: epoch = 0, batch = 419 / 4040 | |
| iter = 419, cls_loss (cur) = 0.494999, cls_loss (avg) = 0.503866, lr = 0.010000 | |
| iter = 419, accuracy (cur) = 0.740000 (all), 0.769231 (pos), 0.708333 (neg) | |
| iter = 419, accuracy (avg) = 0.734791 (all), 0.675347 (pos), 0.794639 (neg) | |
| data reader: epoch = 0, batch = 420 / 4040 | |
| iter = 420, cls_loss (cur) = 0.439844, cls_loss (avg) = 0.503226, lr = 0.010000 | |
| iter = 420, accuracy (cur) = 0.840000 (all), 0.920000 (pos), 0.760000 (neg) | |
| iter = 420, accuracy (avg) = 0.735843 (all), 0.677794 (pos), 0.794292 (neg) | |
| data reader: epoch = 0, batch = 421 / 4040 | |
| iter = 421, cls_loss (cur) = 0.419022, cls_loss (avg) = 0.502384, lr = 0.010000 | |
| iter = 421, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.807692 (neg) | |
| iter = 421, accuracy (avg) = 0.736285 (all), 0.678516 (pos), 0.794426 (neg) | |
| data reader: epoch = 0, batch = 422 / 4040 | |
| iter = 422, cls_loss (cur) = 0.475516, cls_loss (avg) = 0.502115, lr = 0.010000 | |
| iter = 422, accuracy (cur) = 0.840000 (all), 0.850000 (pos), 0.833333 (neg) | |
| iter = 422, accuracy (avg) = 0.737322 (all), 0.680231 (pos), 0.794816 (neg) | |
| data reader: epoch = 0, batch = 423 / 4040 | |
| iter = 423, cls_loss (cur) = 0.459912, cls_loss (avg) = 0.501693, lr = 0.010000 | |
| iter = 423, accuracy (cur) = 0.780000 (all), 0.600000 (pos), 0.960000 (neg) | |
| iter = 423, accuracy (avg) = 0.737749 (all), 0.679428 (pos), 0.796467 (neg) | |
| data reader: epoch = 0, batch = 424 / 4040 | |
| iter = 424, cls_loss (cur) = 0.519936, cls_loss (avg) = 0.501876, lr = 0.010000 | |
| iter = 424, accuracy (cur) = 0.700000 (all), 0.607143 (pos), 0.818182 (neg) | |
| iter = 424, accuracy (avg) = 0.737371 (all), 0.678705 (pos), 0.796684 (neg) | |
| data reader: epoch = 0, batch = 425 / 4040 | |
| iter = 425, cls_loss (cur) = 0.504765, cls_loss (avg) = 0.501905, lr = 0.010000 | |
| iter = 425, accuracy (cur) = 0.740000 (all), 0.653846 (pos), 0.833333 (neg) | |
| iter = 425, accuracy (avg) = 0.737397 (all), 0.678457 (pos), 0.797051 (neg) | |
| data reader: epoch = 0, batch = 426 / 4040 | |
| iter = 426, cls_loss (cur) = 0.432822, cls_loss (avg) = 0.501214, lr = 0.010000 | |
| iter = 426, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 426, accuracy (avg) = 0.737823 (all), 0.679450 (pos), 0.796907 (neg) | |
| data reader: epoch = 0, batch = 427 / 4040 | |
| iter = 427, cls_loss (cur) = 0.457288, cls_loss (avg) = 0.500774, lr = 0.010000 | |
| iter = 427, accuracy (cur) = 0.860000 (all), 0.809524 (pos), 0.896552 (neg) | |
| iter = 427, accuracy (avg) = 0.739045 (all), 0.680751 (pos), 0.797903 (neg) | |
| data reader: epoch = 0, batch = 428 / 4040 | |
| iter = 428, cls_loss (cur) = 0.406655, cls_loss (avg) = 0.499833, lr = 0.010000 | |
| iter = 428, accuracy (cur) = 0.860000 (all), 0.750000 (pos), 0.933333 (neg) | |
| iter = 428, accuracy (avg) = 0.740255 (all), 0.681443 (pos), 0.799257 (neg) | |
| data reader: epoch = 0, batch = 429 / 4040 | |
| iter = 429, cls_loss (cur) = 0.487503, cls_loss (avg) = 0.499710, lr = 0.010000 | |
| iter = 429, accuracy (cur) = 0.820000 (all), 0.687500 (pos), 0.882353 (neg) | |
| iter = 429, accuracy (avg) = 0.741052 (all), 0.681504 (pos), 0.800088 (neg) | |
| data reader: epoch = 0, batch = 430 / 4040 | |
| iter = 430, cls_loss (cur) = 0.471670, cls_loss (avg) = 0.499430, lr = 0.010000 | |
| iter = 430, accuracy (cur) = 0.820000 (all), 0.619048 (pos), 0.965517 (neg) | |
| iter = 430, accuracy (avg) = 0.741842 (all), 0.680879 (pos), 0.801743 (neg) | |
| data reader: epoch = 0, batch = 431 / 4040 | |
| iter = 431, cls_loss (cur) = 0.498589, cls_loss (avg) = 0.499421, lr = 0.010000 | |
| iter = 431, accuracy (cur) = 0.740000 (all), 0.625000 (pos), 0.944444 (neg) | |
| iter = 431, accuracy (avg) = 0.741823 (all), 0.680320 (pos), 0.803170 (neg) | |
| data reader: epoch = 0, batch = 432 / 4040 | |
| iter = 432, cls_loss (cur) = 0.484873, cls_loss (avg) = 0.499276, lr = 0.010000 | |
| iter = 432, accuracy (cur) = 0.780000 (all), 0.740741 (pos), 0.826087 (neg) | |
| iter = 432, accuracy (avg) = 0.742205 (all), 0.680925 (pos), 0.803399 (neg) | |
| data reader: epoch = 0, batch = 433 / 4040 | |
| iter = 433, cls_loss (cur) = 0.453675, cls_loss (avg) = 0.498820, lr = 0.010000 | |
| iter = 433, accuracy (cur) = 0.800000 (all), 0.708333 (pos), 0.884615 (neg) | |
| iter = 433, accuracy (avg) = 0.742783 (all), 0.681199 (pos), 0.804211 (neg) | |
| data reader: epoch = 0, batch = 434 / 4040 | |
| iter = 434, cls_loss (cur) = 0.541386, cls_loss (avg) = 0.499245, lr = 0.010000 | |
| iter = 434, accuracy (cur) = 0.640000 (all), 0.653846 (pos), 0.625000 (neg) | |
| iter = 434, accuracy (avg) = 0.741755 (all), 0.680925 (pos), 0.802419 (neg) | |
| data reader: epoch = 0, batch = 435 / 4040 | |
| iter = 435, cls_loss (cur) = 0.424050, cls_loss (avg) = 0.498493, lr = 0.010000 | |
| iter = 435, accuracy (cur) = 0.860000 (all), 0.826087 (pos), 0.888889 (neg) | |
| iter = 435, accuracy (avg) = 0.742938 (all), 0.682377 (pos), 0.803284 (neg) | |
| data reader: epoch = 0, batch = 436 / 4040 | |
| iter = 436, cls_loss (cur) = 0.525368, cls_loss (avg) = 0.498762, lr = 0.010000 | |
| iter = 436, accuracy (cur) = 0.780000 (all), 0.840000 (pos), 0.720000 (neg) | |
| iter = 436, accuracy (avg) = 0.743308 (all), 0.683953 (pos), 0.802451 (neg) | |
| data reader: epoch = 0, batch = 437 / 4040 | |
| iter = 437, cls_loss (cur) = 0.492989, cls_loss (avg) = 0.498704, lr = 0.010000 | |
| iter = 437, accuracy (cur) = 0.740000 (all), 0.700000 (pos), 0.800000 (neg) | |
| iter = 437, accuracy (avg) = 0.743275 (all), 0.684114 (pos), 0.802426 (neg) | |
| data reader: epoch = 0, batch = 438 / 4040 | |
| iter = 438, cls_loss (cur) = 0.571034, cls_loss (avg) = 0.499428, lr = 0.010000 | |
| iter = 438, accuracy (cur) = 0.780000 (all), 0.695652 (pos), 0.851852 (neg) | |
| iter = 438, accuracy (avg) = 0.743642 (all), 0.684229 (pos), 0.802920 (neg) | |
| data reader: epoch = 0, batch = 439 / 4040 | |
| iter = 439, cls_loss (cur) = 0.365949, cls_loss (avg) = 0.498093, lr = 0.010000 | |
| iter = 439, accuracy (cur) = 0.880000 (all), 0.848485 (pos), 0.941176 (neg) | |
| iter = 439, accuracy (avg) = 0.745006 (all), 0.685871 (pos), 0.804303 (neg) | |
| data reader: epoch = 0, batch = 440 / 4040 | |
| iter = 440, cls_loss (cur) = 0.358607, cls_loss (avg) = 0.496698, lr = 0.010000 | |
| iter = 440, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 440, accuracy (avg) = 0.746356 (all), 0.687902 (pos), 0.804956 (neg) | |
| data reader: epoch = 0, batch = 441 / 4040 | |
| iter = 441, cls_loss (cur) = 0.559548, cls_loss (avg) = 0.497327, lr = 0.010000 | |
| iter = 441, accuracy (cur) = 0.660000 (all), 0.695652 (pos), 0.629630 (neg) | |
| iter = 441, accuracy (avg) = 0.745492 (all), 0.687979 (pos), 0.803202 (neg) | |
| data reader: epoch = 0, batch = 442 / 4040 | |
| iter = 442, cls_loss (cur) = 0.526712, cls_loss (avg) = 0.497620, lr = 0.010000 | |
| iter = 442, accuracy (cur) = 0.780000 (all), 0.720000 (pos), 0.840000 (neg) | |
| iter = 442, accuracy (avg) = 0.745837 (all), 0.688299 (pos), 0.803570 (neg) | |
| data reader: epoch = 0, batch = 443 / 4040 | |
| iter = 443, cls_loss (cur) = 0.416431, cls_loss (avg) = 0.496808, lr = 0.010000 | |
| iter = 443, accuracy (cur) = 0.860000 (all), 0.789474 (pos), 0.903226 (neg) | |
| iter = 443, accuracy (avg) = 0.746979 (all), 0.689311 (pos), 0.804567 (neg) | |
| data reader: epoch = 0, batch = 444 / 4040 | |
| iter = 444, cls_loss (cur) = 0.408652, cls_loss (avg) = 0.495927, lr = 0.010000 | |
| iter = 444, accuracy (cur) = 0.860000 (all), 0.727273 (pos), 0.964286 (neg) | |
| iter = 444, accuracy (avg) = 0.748109 (all), 0.689691 (pos), 0.806164 (neg) | |
| data reader: epoch = 0, batch = 445 / 4040 | |
| iter = 445, cls_loss (cur) = 0.431926, cls_loss (avg) = 0.495287, lr = 0.010000 | |
| iter = 445, accuracy (cur) = 0.800000 (all), 0.739130 (pos), 0.851852 (neg) | |
| iter = 445, accuracy (avg) = 0.748628 (all), 0.690185 (pos), 0.806621 (neg) | |
| data reader: epoch = 0, batch = 446 / 4040 | |
| iter = 446, cls_loss (cur) = 0.468986, cls_loss (avg) = 0.495024, lr = 0.010000 | |
| iter = 446, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.863636 (neg) | |
| iter = 446, accuracy (avg) = 0.749142 (all), 0.690783 (pos), 0.807191 (neg) | |
| data reader: epoch = 0, batch = 447 / 4040 | |
| iter = 447, cls_loss (cur) = 0.485180, cls_loss (avg) = 0.494925, lr = 0.010000 | |
| iter = 447, accuracy (cur) = 0.740000 (all), 0.625000 (pos), 0.944444 (neg) | |
| iter = 447, accuracy (avg) = 0.749050 (all), 0.690125 (pos), 0.808564 (neg) | |
| data reader: epoch = 0, batch = 448 / 4040 | |
| iter = 448, cls_loss (cur) = 0.416123, cls_loss (avg) = 0.494137, lr = 0.010000 | |
| iter = 448, accuracy (cur) = 0.820000 (all), 0.809524 (pos), 0.827586 (neg) | |
| iter = 448, accuracy (avg) = 0.749760 (all), 0.691319 (pos), 0.808754 (neg) | |
| data reader: epoch = 0, batch = 449 / 4040 | |
| iter = 449, cls_loss (cur) = 0.468736, cls_loss (avg) = 0.493883, lr = 0.010000 | |
| iter = 449, accuracy (cur) = 0.760000 (all), 0.846154 (pos), 0.666667 (neg) | |
| iter = 449, accuracy (avg) = 0.749862 (all), 0.692868 (pos), 0.807333 (neg) | |
| data reader: epoch = 0, batch = 450 / 4040 | |
| iter = 450, cls_loss (cur) = 0.555917, cls_loss (avg) = 0.494504, lr = 0.010000 | |
| iter = 450, accuracy (cur) = 0.680000 (all), 0.695652 (pos), 0.666667 (neg) | |
| iter = 450, accuracy (avg) = 0.749164 (all), 0.692896 (pos), 0.805926 (neg) | |
| data reader: epoch = 0, batch = 451 / 4040 | |
| iter = 451, cls_loss (cur) = 0.439344, cls_loss (avg) = 0.493952, lr = 0.010000 | |
| iter = 451, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 451, accuracy (avg) = 0.749872 (all), 0.692923 (pos), 0.807126 (neg) | |
| data reader: epoch = 0, batch = 452 / 4040 | |
| iter = 452, cls_loss (cur) = 0.491219, cls_loss (avg) = 0.493925, lr = 0.010000 | |
| iter = 452, accuracy (cur) = 0.780000 (all), 0.727273 (pos), 0.821429 (neg) | |
| iter = 452, accuracy (avg) = 0.750173 (all), 0.693267 (pos), 0.807269 (neg) | |
| data reader: epoch = 0, batch = 453 / 4040 | |
| iter = 453, cls_loss (cur) = 0.439103, cls_loss (avg) = 0.493377, lr = 0.010000 | |
| iter = 453, accuracy (cur) = 0.820000 (all), 0.666667 (pos), 0.961538 (neg) | |
| iter = 453, accuracy (avg) = 0.750872 (all), 0.693001 (pos), 0.808812 (neg) | |
| data reader: epoch = 0, batch = 454 / 4040 | |
| iter = 454, cls_loss (cur) = 0.458850, cls_loss (avg) = 0.493031, lr = 0.010000 | |
| iter = 454, accuracy (cur) = 0.760000 (all), 0.642857 (pos), 0.909091 (neg) | |
| iter = 454, accuracy (avg) = 0.750963 (all), 0.692499 (pos), 0.809815 (neg) | |
| data reader: epoch = 0, batch = 455 / 4040 | |
| iter = 455, cls_loss (cur) = 0.501373, cls_loss (avg) = 0.493115, lr = 0.010000 | |
| iter = 455, accuracy (cur) = 0.820000 (all), 0.740741 (pos), 0.913043 (neg) | |
| iter = 455, accuracy (avg) = 0.751653 (all), 0.692982 (pos), 0.810847 (neg) | |
| data reader: epoch = 0, batch = 456 / 4040 | |
| iter = 456, cls_loss (cur) = 0.481003, cls_loss (avg) = 0.492994, lr = 0.010000 | |
| iter = 456, accuracy (cur) = 0.760000 (all), 0.730769 (pos), 0.791667 (neg) | |
| iter = 456, accuracy (avg) = 0.751737 (all), 0.693360 (pos), 0.810655 (neg) | |
| data reader: epoch = 0, batch = 457 / 4040 | |
| iter = 457, cls_loss (cur) = 0.396640, cls_loss (avg) = 0.492030, lr = 0.010000 | |
| iter = 457, accuracy (cur) = 0.820000 (all), 0.875000 (pos), 0.769231 (neg) | |
| iter = 457, accuracy (avg) = 0.752419 (all), 0.695176 (pos), 0.810241 (neg) | |
| data reader: epoch = 0, batch = 458 / 4040 | |
| iter = 458, cls_loss (cur) = 0.431085, cls_loss (avg) = 0.491421, lr = 0.010000 | |
| iter = 458, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 458, accuracy (avg) = 0.753495 (all), 0.696686 (pos), 0.810889 (neg) | |
| data reader: epoch = 0, batch = 459 / 4040 | |
| iter = 459, cls_loss (cur) = 0.511185, cls_loss (avg) = 0.491618, lr = 0.010000 | |
| iter = 459, accuracy (cur) = 0.780000 (all), 0.823529 (pos), 0.757576 (neg) | |
| iter = 459, accuracy (avg) = 0.753760 (all), 0.697954 (pos), 0.810356 (neg) | |
| data reader: epoch = 0, batch = 460 / 4040 | |
| iter = 460, cls_loss (cur) = 0.504469, cls_loss (avg) = 0.491747, lr = 0.010000 | |
| iter = 460, accuracy (cur) = 0.700000 (all), 0.545455 (pos), 0.821429 (neg) | |
| iter = 460, accuracy (avg) = 0.753223 (all), 0.696429 (pos), 0.810466 (neg) | |
| data reader: epoch = 0, batch = 461 / 4040 | |
| iter = 461, cls_loss (cur) = 0.552171, cls_loss (avg) = 0.492351, lr = 0.010000 | |
| iter = 461, accuracy (cur) = 0.740000 (all), 0.633333 (pos), 0.900000 (neg) | |
| iter = 461, accuracy (avg) = 0.753090 (all), 0.695798 (pos), 0.811362 (neg) | |
| data reader: epoch = 0, batch = 462 / 4040 | |
| iter = 462, cls_loss (cur) = 0.466362, cls_loss (avg) = 0.492091, lr = 0.010000 | |
| iter = 462, accuracy (cur) = 0.780000 (all), 0.869565 (pos), 0.703704 (neg) | |
| iter = 462, accuracy (avg) = 0.753359 (all), 0.697536 (pos), 0.810285 (neg) | |
| data reader: epoch = 0, batch = 463 / 4040 | |
| iter = 463, cls_loss (cur) = 0.481452, cls_loss (avg) = 0.491985, lr = 0.010000 | |
| iter = 463, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.807692 (neg) | |
| iter = 463, accuracy (avg) = 0.753626 (all), 0.698060 (pos), 0.810259 (neg) | |
| data reader: epoch = 0, batch = 464 / 4040 | |
| iter = 464, cls_loss (cur) = 0.445313, cls_loss (avg) = 0.491518, lr = 0.010000 | |
| iter = 464, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.913043 (neg) | |
| iter = 464, accuracy (avg) = 0.753890 (all), 0.697747 (pos), 0.811287 (neg) | |
| data reader: epoch = 0, batch = 465 / 4040 | |
| iter = 465, cls_loss (cur) = 0.468406, cls_loss (avg) = 0.491287, lr = 0.010000 | |
| iter = 465, accuracy (cur) = 0.760000 (all), 0.791667 (pos), 0.730769 (neg) | |
| iter = 465, accuracy (avg) = 0.753951 (all), 0.698686 (pos), 0.810482 (neg) | |
| data reader: epoch = 0, batch = 466 / 4040 | |
| iter = 466, cls_loss (cur) = 0.419416, cls_loss (avg) = 0.490568, lr = 0.010000 | |
| iter = 466, accuracy (cur) = 0.780000 (all), 0.650000 (pos), 0.866667 (neg) | |
| iter = 466, accuracy (avg) = 0.754211 (all), 0.698199 (pos), 0.811044 (neg) | |
| data reader: epoch = 0, batch = 467 / 4040 | |
| iter = 467, cls_loss (cur) = 0.469301, cls_loss (avg) = 0.490356, lr = 0.010000 | |
| iter = 467, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.827586 (neg) | |
| iter = 467, accuracy (avg) = 0.754269 (all), 0.697884 (pos), 0.811209 (neg) | |
| data reader: epoch = 0, batch = 468 / 4040 | |
| iter = 468, cls_loss (cur) = 0.454313, cls_loss (avg) = 0.489995, lr = 0.010000 | |
| iter = 468, accuracy (cur) = 0.780000 (all), 0.629630 (pos), 0.956522 (neg) | |
| iter = 468, accuracy (avg) = 0.754526 (all), 0.697201 (pos), 0.812662 (neg) | |
| data reader: epoch = 0, batch = 469 / 4040 | |
| iter = 469, cls_loss (cur) = 0.369680, cls_loss (avg) = 0.488792, lr = 0.010000 | |
| iter = 469, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 469, accuracy (avg) = 0.755581 (all), 0.698979 (pos), 0.812997 (neg) | |
| data reader: epoch = 0, batch = 470 / 4040 | |
| iter = 470, cls_loss (cur) = 0.469101, cls_loss (avg) = 0.488595, lr = 0.010000 | |
| iter = 470, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 470, accuracy (avg) = 0.756425 (all), 0.699920 (pos), 0.813915 (neg) | |
| data reader: epoch = 0, batch = 471 / 4040 | |
| iter = 471, cls_loss (cur) = 0.499330, cls_loss (avg) = 0.488702, lr = 0.010000 | |
| iter = 471, accuracy (cur) = 0.800000 (all), 0.851852 (pos), 0.739130 (neg) | |
| iter = 471, accuracy (avg) = 0.756861 (all), 0.701440 (pos), 0.813167 (neg) | |
| data reader: epoch = 0, batch = 472 / 4040 | |
| iter = 472, cls_loss (cur) = 0.482226, cls_loss (avg) = 0.488638, lr = 0.010000 | |
| iter = 472, accuracy (cur) = 0.780000 (all), 0.590909 (pos), 0.928571 (neg) | |
| iter = 472, accuracy (avg) = 0.757092 (all), 0.700334 (pos), 0.814321 (neg) | |
| data reader: epoch = 0, batch = 473 / 4040 | |
| iter = 473, cls_loss (cur) = 0.472341, cls_loss (avg) = 0.488475, lr = 0.010000 | |
| iter = 473, accuracy (cur) = 0.720000 (all), 0.692308 (pos), 0.750000 (neg) | |
| iter = 473, accuracy (avg) = 0.756722 (all), 0.700254 (pos), 0.813678 (neg) | |
| data reader: epoch = 0, batch = 474 / 4040 | |
| iter = 474, cls_loss (cur) = 0.309531, cls_loss (avg) = 0.486685, lr = 0.010000 | |
| iter = 474, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 474, accuracy (avg) = 0.757754 (all), 0.701328 (pos), 0.814708 (neg) | |
| data reader: epoch = 0, batch = 475 / 4040 | |
| iter = 475, cls_loss (cur) = 0.371081, cls_loss (avg) = 0.485529, lr = 0.010000 | |
| iter = 475, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 475, accuracy (avg) = 0.758977 (all), 0.703446 (pos), 0.815079 (neg) | |
| data reader: epoch = 0, batch = 476 / 4040 | |
| iter = 476, cls_loss (cur) = 0.372357, cls_loss (avg) = 0.484398, lr = 0.010000 | |
| iter = 476, accuracy (cur) = 0.840000 (all), 0.923077 (pos), 0.750000 (neg) | |
| iter = 476, accuracy (avg) = 0.759787 (all), 0.705642 (pos), 0.814428 (neg) | |
| data reader: epoch = 0, batch = 477 / 4040 | |
| iter = 477, cls_loss (cur) = 0.522925, cls_loss (avg) = 0.484783, lr = 0.010000 | |
| iter = 477, accuracy (cur) = 0.680000 (all), 0.541667 (pos), 0.807692 (neg) | |
| iter = 477, accuracy (avg) = 0.758989 (all), 0.704002 (pos), 0.814361 (neg) | |
| data reader: epoch = 0, batch = 478 / 4040 | |
| iter = 478, cls_loss (cur) = 0.486623, cls_loss (avg) = 0.484801, lr = 0.010000 | |
| iter = 478, accuracy (cur) = 0.700000 (all), 0.541667 (pos), 0.846154 (neg) | |
| iter = 478, accuracy (avg) = 0.758399 (all), 0.702379 (pos), 0.814679 (neg) | |
| data reader: epoch = 0, batch = 479 / 4040 | |
| iter = 479, cls_loss (cur) = 0.430706, cls_loss (avg) = 0.484260, lr = 0.010000 | |
| iter = 479, accuracy (cur) = 0.800000 (all), 0.782609 (pos), 0.814815 (neg) | |
| iter = 479, accuracy (avg) = 0.758815 (all), 0.703181 (pos), 0.814680 (neg) | |
| data reader: epoch = 0, batch = 480 / 4040 | |
| iter = 480, cls_loss (cur) = 0.421628, cls_loss (avg) = 0.483634, lr = 0.010000 | |
| iter = 480, accuracy (cur) = 0.780000 (all), 0.636364 (pos), 0.892857 (neg) | |
| iter = 480, accuracy (avg) = 0.759027 (all), 0.702513 (pos), 0.815462 (neg) | |
| data reader: epoch = 0, batch = 481 / 4040 | |
| iter = 481, cls_loss (cur) = 0.434262, cls_loss (avg) = 0.483140, lr = 0.010000 | |
| iter = 481, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.850000 (neg) | |
| iter = 481, accuracy (avg) = 0.759637 (all), 0.703488 (pos), 0.815807 (neg) | |
| data reader: epoch = 0, batch = 482 / 4040 | |
| iter = 482, cls_loss (cur) = 0.407822, cls_loss (avg) = 0.482387, lr = 0.010000 | |
| iter = 482, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 482, accuracy (avg) = 0.760640 (all), 0.704453 (pos), 0.816849 (neg) | |
| data reader: epoch = 0, batch = 483 / 4040 | |
| iter = 483, cls_loss (cur) = 0.394958, cls_loss (avg) = 0.481513, lr = 0.010000 | |
| iter = 483, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 483, accuracy (avg) = 0.761634 (all), 0.706104 (pos), 0.817199 (neg) | |
| data reader: epoch = 0, batch = 484 / 4040 | |
| iter = 484, cls_loss (cur) = 0.454867, cls_loss (avg) = 0.481246, lr = 0.010000 | |
| iter = 484, accuracy (cur) = 0.820000 (all), 0.809524 (pos), 0.827586 (neg) | |
| iter = 484, accuracy (avg) = 0.762218 (all), 0.707138 (pos), 0.817303 (neg) | |
| data reader: epoch = 0, batch = 485 / 4040 | |
| iter = 485, cls_loss (cur) = 0.408930, cls_loss (avg) = 0.480523, lr = 0.010000 | |
| iter = 485, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.840000 (neg) | |
| iter = 485, accuracy (avg) = 0.762796 (all), 0.708067 (pos), 0.817530 (neg) | |
| data reader: epoch = 0, batch = 486 / 4040 | |
| iter = 486, cls_loss (cur) = 0.473833, cls_loss (avg) = 0.480456, lr = 0.010000 | |
| iter = 486, accuracy (cur) = 0.760000 (all), 0.642857 (pos), 0.909091 (neg) | |
| iter = 486, accuracy (avg) = 0.762768 (all), 0.707415 (pos), 0.818446 (neg) | |
| data reader: epoch = 0, batch = 487 / 4040 | |
| iter = 487, cls_loss (cur) = 0.433892, cls_loss (avg) = 0.479991, lr = 0.010000 | |
| iter = 487, accuracy (cur) = 0.760000 (all), 0.709677 (pos), 0.842105 (neg) | |
| iter = 487, accuracy (avg) = 0.762740 (all), 0.707437 (pos), 0.818682 (neg) | |
| data reader: epoch = 0, batch = 488 / 4040 | |
| iter = 488, cls_loss (cur) = 0.461846, cls_loss (avg) = 0.479809, lr = 0.010000 | |
| iter = 488, accuracy (cur) = 0.780000 (all), 0.703704 (pos), 0.869565 (neg) | |
| iter = 488, accuracy (avg) = 0.762913 (all), 0.707400 (pos), 0.819191 (neg) | |
| data reader: epoch = 0, batch = 489 / 4040 | |
| iter = 489, cls_loss (cur) = 0.414787, cls_loss (avg) = 0.479159, lr = 0.010000 | |
| iter = 489, accuracy (cur) = 0.780000 (all), 0.791667 (pos), 0.769231 (neg) | |
| iter = 489, accuracy (avg) = 0.763083 (all), 0.708243 (pos), 0.818692 (neg) | |
| data reader: epoch = 0, batch = 490 / 4040 | |
| iter = 490, cls_loss (cur) = 0.377254, cls_loss (avg) = 0.478140, lr = 0.010000 | |
| iter = 490, accuracy (cur) = 0.800000 (all), 0.709677 (pos), 0.947368 (neg) | |
| iter = 490, accuracy (avg) = 0.763453 (all), 0.708257 (pos), 0.819978 (neg) | |
| data reader: epoch = 0, batch = 491 / 4040 | |
| iter = 491, cls_loss (cur) = 0.521362, cls_loss (avg) = 0.478572, lr = 0.010000 | |
| iter = 491, accuracy (cur) = 0.720000 (all), 0.812500 (pos), 0.555556 (neg) | |
| iter = 491, accuracy (avg) = 0.763018 (all), 0.709299 (pos), 0.817334 (neg) | |
| data reader: epoch = 0, batch = 492 / 4040 | |
| iter = 492, cls_loss (cur) = 0.630768, cls_loss (avg) = 0.480094, lr = 0.010000 | |
| iter = 492, accuracy (cur) = 0.580000 (all), 0.888889 (pos), 0.406250 (neg) | |
| iter = 492, accuracy (avg) = 0.761188 (all), 0.711095 (pos), 0.813223 (neg) | |
| data reader: epoch = 0, batch = 493 / 4040 | |
| iter = 493, cls_loss (cur) = 0.447621, cls_loss (avg) = 0.479769, lr = 0.010000 | |
| iter = 493, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 493, accuracy (avg) = 0.761776 (all), 0.712199 (pos), 0.813273 (neg) | |
| data reader: epoch = 0, batch = 494 / 4040 | |
| iter = 494, cls_loss (cur) = 0.376275, cls_loss (avg) = 0.478734, lr = 0.010000 | |
| iter = 494, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 494, accuracy (avg) = 0.762758 (all), 0.713697 (pos), 0.813712 (neg) | |
| data reader: epoch = 0, batch = 495 / 4040 | |
| iter = 495, cls_loss (cur) = 0.579830, cls_loss (avg) = 0.479745, lr = 0.010000 | |
| iter = 495, accuracy (cur) = 0.700000 (all), 0.750000 (pos), 0.653846 (neg) | |
| iter = 495, accuracy (avg) = 0.762131 (all), 0.714060 (pos), 0.812113 (neg) | |
| data reader: epoch = 0, batch = 496 / 4040 | |
| iter = 496, cls_loss (cur) = 0.387619, cls_loss (avg) = 0.478824, lr = 0.010000 | |
| iter = 496, accuracy (cur) = 0.860000 (all), 0.785714 (pos), 0.954545 (neg) | |
| iter = 496, accuracy (avg) = 0.763109 (all), 0.714777 (pos), 0.813537 (neg) | |
| data reader: epoch = 0, batch = 497 / 4040 | |
| iter = 497, cls_loss (cur) = 0.473415, cls_loss (avg) = 0.478770, lr = 0.010000 | |
| iter = 497, accuracy (cur) = 0.760000 (all), 0.629630 (pos), 0.913043 (neg) | |
| iter = 497, accuracy (avg) = 0.763078 (all), 0.713925 (pos), 0.814532 (neg) | |
| data reader: epoch = 0, batch = 498 / 4040 | |
| iter = 498, cls_loss (cur) = 0.368431, cls_loss (avg) = 0.477667, lr = 0.010000 | |
| iter = 498, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 498, accuracy (avg) = 0.763647 (all), 0.713743 (pos), 0.815646 (neg) | |
| data reader: epoch = 0, batch = 499 / 4040 | |
| iter = 499, cls_loss (cur) = 0.384113, cls_loss (avg) = 0.476731, lr = 0.010000 | |
| iter = 499, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 499, accuracy (avg) = 0.764411 (all), 0.714682 (pos), 0.816240 (neg) | |
| data reader: epoch = 0, batch = 500 / 4040 | |
| iter = 500, cls_loss (cur) = 0.471564, cls_loss (avg) = 0.476679, lr = 0.010000 | |
| iter = 500, accuracy (cur) = 0.800000 (all), 0.777778 (pos), 0.812500 (neg) | |
| iter = 500, accuracy (avg) = 0.764767 (all), 0.715313 (pos), 0.816202 (neg) | |
| data reader: epoch = 0, batch = 501 / 4040 | |
| iter = 501, cls_loss (cur) = 0.446424, cls_loss (avg) = 0.476377, lr = 0.010000 | |
| iter = 501, accuracy (cur) = 0.780000 (all), 0.724138 (pos), 0.857143 (neg) | |
| iter = 501, accuracy (avg) = 0.764919 (all), 0.715401 (pos), 0.816612 (neg) | |
| data reader: epoch = 0, batch = 502 / 4040 | |
| iter = 502, cls_loss (cur) = 0.414731, cls_loss (avg) = 0.475760, lr = 0.010000 | |
| iter = 502, accuracy (cur) = 0.840000 (all), 0.739130 (pos), 0.925926 (neg) | |
| iter = 502, accuracy (avg) = 0.765670 (all), 0.715639 (pos), 0.817705 (neg) | |
| data reader: epoch = 0, batch = 503 / 4040 | |
| iter = 503, cls_loss (cur) = 0.478607, cls_loss (avg) = 0.475789, lr = 0.010000 | |
| iter = 503, accuracy (cur) = 0.760000 (all), 0.740741 (pos), 0.782609 (neg) | |
| iter = 503, accuracy (avg) = 0.765613 (all), 0.715890 (pos), 0.817354 (neg) | |
| data reader: epoch = 0, batch = 504 / 4040 | |
| iter = 504, cls_loss (cur) = 0.425217, cls_loss (avg) = 0.475283, lr = 0.010000 | |
| iter = 504, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 504, accuracy (avg) = 0.766957 (all), 0.717898 (pos), 0.818027 (neg) | |
| data reader: epoch = 0, batch = 505 / 4040 | |
| iter = 505, cls_loss (cur) = 0.479401, cls_loss (avg) = 0.475324, lr = 0.010000 | |
| iter = 505, accuracy (cur) = 0.760000 (all), 0.777778 (pos), 0.739130 (neg) | |
| iter = 505, accuracy (avg) = 0.766888 (all), 0.718496 (pos), 0.817238 (neg) | |
| data reader: epoch = 0, batch = 506 / 4040 | |
| iter = 506, cls_loss (cur) = 0.464091, cls_loss (avg) = 0.475212, lr = 0.010000 | |
| iter = 506, accuracy (cur) = 0.800000 (all), 0.880000 (pos), 0.720000 (neg) | |
| iter = 506, accuracy (avg) = 0.767219 (all), 0.720111 (pos), 0.816265 (neg) | |
| data reader: epoch = 0, batch = 507 / 4040 | |
| iter = 507, cls_loss (cur) = 0.426067, cls_loss (avg) = 0.474721, lr = 0.010000 | |
| iter = 507, accuracy (cur) = 0.860000 (all), 0.950000 (pos), 0.800000 (neg) | |
| iter = 507, accuracy (avg) = 0.768147 (all), 0.722410 (pos), 0.816103 (neg) | |
| data reader: epoch = 0, batch = 508 / 4040 | |
| iter = 508, cls_loss (cur) = 0.409058, cls_loss (avg) = 0.474064, lr = 0.010000 | |
| iter = 508, accuracy (cur) = 0.820000 (all), 0.666667 (pos), 1.000000 (neg) | |
| iter = 508, accuracy (avg) = 0.768665 (all), 0.721853 (pos), 0.817942 (neg) | |
| data reader: epoch = 0, batch = 509 / 4040 | |
| iter = 509, cls_loss (cur) = 0.505273, cls_loss (avg) = 0.474376, lr = 0.010000 | |
| iter = 509, accuracy (cur) = 0.740000 (all), 0.695652 (pos), 0.777778 (neg) | |
| iter = 509, accuracy (avg) = 0.768378 (all), 0.721591 (pos), 0.817540 (neg) | |
| data reader: epoch = 0, batch = 510 / 4040 | |
| iter = 510, cls_loss (cur) = 0.335232, cls_loss (avg) = 0.472985, lr = 0.010000 | |
| iter = 510, accuracy (cur) = 0.900000 (all), 0.880000 (pos), 0.920000 (neg) | |
| iter = 510, accuracy (avg) = 0.769695 (all), 0.723175 (pos), 0.818564 (neg) | |
| data reader: epoch = 0, batch = 511 / 4040 | |
| iter = 511, cls_loss (cur) = 0.439600, cls_loss (avg) = 0.472651, lr = 0.010000 | |
| iter = 511, accuracy (cur) = 0.780000 (all), 0.791667 (pos), 0.769231 (neg) | |
| iter = 511, accuracy (avg) = 0.769798 (all), 0.723860 (pos), 0.818071 (neg) | |
| data reader: epoch = 0, batch = 512 / 4040 | |
| iter = 512, cls_loss (cur) = 0.435172, cls_loss (avg) = 0.472276, lr = 0.010000 | |
| iter = 512, accuracy (cur) = 0.740000 (all), 0.571429 (pos), 0.954545 (neg) | |
| iter = 512, accuracy (avg) = 0.769500 (all), 0.722336 (pos), 0.819436 (neg) | |
| data reader: epoch = 0, batch = 513 / 4040 | |
| iter = 513, cls_loss (cur) = 0.517954, cls_loss (avg) = 0.472733, lr = 0.010000 | |
| iter = 513, accuracy (cur) = 0.720000 (all), 0.772727 (pos), 0.678571 (neg) | |
| iter = 513, accuracy (avg) = 0.769005 (all), 0.722839 (pos), 0.818027 (neg) | |
| data reader: epoch = 0, batch = 514 / 4040 | |
| iter = 514, cls_loss (cur) = 0.409330, cls_loss (avg) = 0.472099, lr = 0.010000 | |
| iter = 514, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 514, accuracy (avg) = 0.769515 (all), 0.722568 (pos), 0.819106 (neg) | |
| data reader: epoch = 0, batch = 515 / 4040 | |
| iter = 515, cls_loss (cur) = 0.453332, cls_loss (avg) = 0.471911, lr = 0.010000 | |
| iter = 515, accuracy (cur) = 0.740000 (all), 0.642857 (pos), 0.863636 (neg) | |
| iter = 515, accuracy (avg) = 0.769220 (all), 0.721770 (pos), 0.819552 (neg) | |
| data reader: epoch = 0, batch = 516 / 4040 | |
| iter = 516, cls_loss (cur) = 0.489809, cls_loss (avg) = 0.472090, lr = 0.010000 | |
| iter = 516, accuracy (cur) = 0.760000 (all), 0.789474 (pos), 0.741935 (neg) | |
| iter = 516, accuracy (avg) = 0.769127 (all), 0.722447 (pos), 0.818775 (neg) | |
| data reader: epoch = 0, batch = 517 / 4040 | |
| iter = 517, cls_loss (cur) = 0.452014, cls_loss (avg) = 0.471889, lr = 0.010000 | |
| iter = 517, accuracy (cur) = 0.820000 (all), 0.684211 (pos), 0.903226 (neg) | |
| iter = 517, accuracy (avg) = 0.769636 (all), 0.722065 (pos), 0.819620 (neg) | |
| data reader: epoch = 0, batch = 518 / 4040 | |
| iter = 518, cls_loss (cur) = 0.457643, cls_loss (avg) = 0.471747, lr = 0.010000 | |
| iter = 518, accuracy (cur) = 0.820000 (all), 0.730769 (pos), 0.916667 (neg) | |
| iter = 518, accuracy (avg) = 0.770140 (all), 0.722152 (pos), 0.820590 (neg) | |
| data reader: epoch = 0, batch = 519 / 4040 | |
| iter = 519, cls_loss (cur) = 0.439218, cls_loss (avg) = 0.471421, lr = 0.010000 | |
| iter = 519, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.833333 (neg) | |
| iter = 519, accuracy (avg) = 0.770238 (all), 0.722431 (pos), 0.820718 (neg) | |
| data reader: epoch = 0, batch = 520 / 4040 | |
| iter = 520, cls_loss (cur) = 0.477295, cls_loss (avg) = 0.471480, lr = 0.010000 | |
| iter = 520, accuracy (cur) = 0.840000 (all), 0.880000 (pos), 0.800000 (neg) | |
| iter = 520, accuracy (avg) = 0.770936 (all), 0.724006 (pos), 0.820511 (neg) | |
| data reader: epoch = 0, batch = 521 / 4040 | |
| iter = 521, cls_loss (cur) = 0.470033, cls_loss (avg) = 0.471466, lr = 0.010000 | |
| iter = 521, accuracy (cur) = 0.840000 (all), 0.958333 (pos), 0.730769 (neg) | |
| iter = 521, accuracy (avg) = 0.771627 (all), 0.726350 (pos), 0.819613 (neg) | |
| data reader: epoch = 0, batch = 522 / 4040 | |
| iter = 522, cls_loss (cur) = 0.498157, cls_loss (avg) = 0.471733, lr = 0.010000 | |
| iter = 522, accuracy (cur) = 0.780000 (all), 0.827586 (pos), 0.714286 (neg) | |
| iter = 522, accuracy (avg) = 0.771710 (all), 0.727362 (pos), 0.818560 (neg) | |
| data reader: epoch = 0, batch = 523 / 4040 | |
| iter = 523, cls_loss (cur) = 0.385064, cls_loss (avg) = 0.470866, lr = 0.010000 | |
| iter = 523, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.777778 (neg) | |
| iter = 523, accuracy (avg) = 0.772393 (all), 0.728838 (pos), 0.818152 (neg) | |
| data reader: epoch = 0, batch = 524 / 4040 | |
| iter = 524, cls_loss (cur) = 0.451076, cls_loss (avg) = 0.470668, lr = 0.010000 | |
| iter = 524, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.766667 (neg) | |
| iter = 524, accuracy (avg) = 0.772469 (all), 0.729550 (pos), 0.817637 (neg) | |
| data reader: epoch = 0, batch = 525 / 4040 | |
| iter = 525, cls_loss (cur) = 0.399369, cls_loss (avg) = 0.469955, lr = 0.010000 | |
| iter = 525, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 525, accuracy (avg) = 0.773545 (all), 0.731485 (pos), 0.817794 (neg) | |
| data reader: epoch = 0, batch = 526 / 4040 | |
| iter = 526, cls_loss (cur) = 0.527086, cls_loss (avg) = 0.470526, lr = 0.010000 | |
| iter = 526, accuracy (cur) = 0.700000 (all), 0.500000 (pos), 0.857143 (neg) | |
| iter = 526, accuracy (avg) = 0.772809 (all), 0.729170 (pos), 0.818188 (neg) | |
| data reader: epoch = 0, batch = 527 / 4040 | |
| iter = 527, cls_loss (cur) = 0.414545, cls_loss (avg) = 0.469967, lr = 0.010000 | |
| iter = 527, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 527, accuracy (avg) = 0.773681 (all), 0.729879 (pos), 0.819206 (neg) | |
| data reader: epoch = 0, batch = 528 / 4040 | |
| iter = 528, cls_loss (cur) = 0.474251, cls_loss (avg) = 0.470009, lr = 0.010000 | |
| iter = 528, accuracy (cur) = 0.720000 (all), 0.620690 (pos), 0.857143 (neg) | |
| iter = 528, accuracy (avg) = 0.773144 (all), 0.728787 (pos), 0.819585 (neg) | |
| data reader: epoch = 0, batch = 529 / 4040 | |
| iter = 529, cls_loss (cur) = 0.352429, cls_loss (avg) = 0.468834, lr = 0.010000 | |
| iter = 529, accuracy (cur) = 0.860000 (all), 0.750000 (pos), 0.961538 (neg) | |
| iter = 529, accuracy (avg) = 0.774013 (all), 0.728999 (pos), 0.821005 (neg) | |
| data reader: epoch = 0, batch = 530 / 4040 | |
| iter = 530, cls_loss (cur) = 0.361261, cls_loss (avg) = 0.467758, lr = 0.010000 | |
| iter = 530, accuracy (cur) = 0.800000 (all), 0.653846 (pos), 0.958333 (neg) | |
| iter = 530, accuracy (avg) = 0.774273 (all), 0.728247 (pos), 0.822378 (neg) | |
| data reader: epoch = 0, batch = 531 / 4040 | |
| iter = 531, cls_loss (cur) = 0.515233, cls_loss (avg) = 0.468233, lr = 0.010000 | |
| iter = 531, accuracy (cur) = 0.700000 (all), 0.678571 (pos), 0.727273 (neg) | |
| iter = 531, accuracy (avg) = 0.773530 (all), 0.727751 (pos), 0.821427 (neg) | |
| data reader: epoch = 0, batch = 532 / 4040 | |
| iter = 532, cls_loss (cur) = 0.344268, cls_loss (avg) = 0.466993, lr = 0.010000 | |
| iter = 532, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.950000 (neg) | |
| iter = 532, accuracy (avg) = 0.774395 (all), 0.728473 (pos), 0.822713 (neg) | |
| data reader: epoch = 0, batch = 533 / 4040 | |
| iter = 533, cls_loss (cur) = 0.469826, cls_loss (avg) = 0.467021, lr = 0.010000 | |
| iter = 533, accuracy (cur) = 0.780000 (all), 0.769231 (pos), 0.791667 (neg) | |
| iter = 533, accuracy (avg) = 0.774451 (all), 0.728881 (pos), 0.822402 (neg) | |
| data reader: epoch = 0, batch = 534 / 4040 | |
| iter = 534, cls_loss (cur) = 0.471765, cls_loss (avg) = 0.467069, lr = 0.010000 | |
| iter = 534, accuracy (cur) = 0.720000 (all), 0.850000 (pos), 0.633333 (neg) | |
| iter = 534, accuracy (avg) = 0.773906 (all), 0.730092 (pos), 0.820512 (neg) | |
| data reader: epoch = 0, batch = 535 / 4040 | |
| iter = 535, cls_loss (cur) = 0.422427, cls_loss (avg) = 0.466622, lr = 0.010000 | |
| iter = 535, accuracy (cur) = 0.820000 (all), 0.714286 (pos), 0.896552 (neg) | |
| iter = 535, accuracy (avg) = 0.774367 (all), 0.729934 (pos), 0.821272 (neg) | |
| data reader: epoch = 0, batch = 536 / 4040 | |
| iter = 536, cls_loss (cur) = 0.284467, cls_loss (avg) = 0.464801, lr = 0.010000 | |
| iter = 536, accuracy (cur) = 0.940000 (all), 0.903226 (pos), 1.000000 (neg) | |
| iter = 536, accuracy (avg) = 0.776023 (all), 0.731667 (pos), 0.823059 (neg) | |
| data reader: epoch = 0, batch = 537 / 4040 | |
| iter = 537, cls_loss (cur) = 0.405266, cls_loss (avg) = 0.464205, lr = 0.010000 | |
| iter = 537, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.827586 (neg) | |
| iter = 537, accuracy (avg) = 0.776663 (all), 0.732922 (pos), 0.823104 (neg) | |
| data reader: epoch = 0, batch = 538 / 4040 | |
| iter = 538, cls_loss (cur) = 0.506587, cls_loss (avg) = 0.464629, lr = 0.010000 | |
| iter = 538, accuracy (cur) = 0.620000 (all), 0.500000 (pos), 0.772727 (neg) | |
| iter = 538, accuracy (avg) = 0.775097 (all), 0.730592 (pos), 0.822601 (neg) | |
| data reader: epoch = 0, batch = 539 / 4040 | |
| iter = 539, cls_loss (cur) = 0.452227, cls_loss (avg) = 0.464505, lr = 0.010000 | |
| iter = 539, accuracy (cur) = 0.760000 (all), 0.800000 (pos), 0.720000 (neg) | |
| iter = 539, accuracy (avg) = 0.774946 (all), 0.731286 (pos), 0.821575 (neg) | |
| data reader: epoch = 0, batch = 540 / 4040 | |
| iter = 540, cls_loss (cur) = 0.482966, cls_loss (avg) = 0.464690, lr = 0.010000 | |
| iter = 540, accuracy (cur) = 0.760000 (all), 0.680000 (pos), 0.840000 (neg) | |
| iter = 540, accuracy (avg) = 0.774796 (all), 0.730774 (pos), 0.821759 (neg) | |
| data reader: epoch = 0, batch = 541 / 4040 | |
| iter = 541, cls_loss (cur) = 0.359791, cls_loss (avg) = 0.463641, lr = 0.010000 | |
| iter = 541, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 541, accuracy (avg) = 0.775248 (all), 0.731158 (pos), 0.822291 (neg) | |
| data reader: epoch = 0, batch = 542 / 4040 | |
| iter = 542, cls_loss (cur) = 0.505558, cls_loss (avg) = 0.464060, lr = 0.010000 | |
| iter = 542, accuracy (cur) = 0.700000 (all), 0.521739 (pos), 0.851852 (neg) | |
| iter = 542, accuracy (avg) = 0.774496 (all), 0.729064 (pos), 0.822587 (neg) | |
| data reader: epoch = 0, batch = 543 / 4040 | |
| iter = 543, cls_loss (cur) = 0.499102, cls_loss (avg) = 0.464410, lr = 0.010000 | |
| iter = 543, accuracy (cur) = 0.720000 (all), 0.720000 (pos), 0.720000 (neg) | |
| iter = 543, accuracy (avg) = 0.773951 (all), 0.728973 (pos), 0.821561 (neg) | |
| data reader: epoch = 0, batch = 544 / 4040 | |
| iter = 544, cls_loss (cur) = 0.401887, cls_loss (avg) = 0.463785, lr = 0.010000 | |
| iter = 544, accuracy (cur) = 0.840000 (all), 0.920000 (pos), 0.760000 (neg) | |
| iter = 544, accuracy (avg) = 0.774611 (all), 0.730884 (pos), 0.820945 (neg) | |
| data reader: epoch = 0, batch = 545 / 4040 | |
| iter = 545, cls_loss (cur) = 0.364302, cls_loss (avg) = 0.462790, lr = 0.010000 | |
| iter = 545, accuracy (cur) = 0.860000 (all), 0.758621 (pos), 1.000000 (neg) | |
| iter = 545, accuracy (avg) = 0.775465 (all), 0.731161 (pos), 0.822736 (neg) | |
| data reader: epoch = 0, batch = 546 / 4040 | |
| iter = 546, cls_loss (cur) = 0.422158, cls_loss (avg) = 0.462384, lr = 0.010000 | |
| iter = 546, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 546, accuracy (avg) = 0.776110 (all), 0.731926 (pos), 0.823259 (neg) | |
| data reader: epoch = 0, batch = 547 / 4040 | |
| iter = 547, cls_loss (cur) = 0.443687, cls_loss (avg) = 0.462197, lr = 0.010000 | |
| iter = 547, accuracy (cur) = 0.780000 (all), 0.724138 (pos), 0.857143 (neg) | |
| iter = 547, accuracy (avg) = 0.776149 (all), 0.731848 (pos), 0.823598 (neg) | |
| data reader: epoch = 0, batch = 548 / 4040 | |
| iter = 548, cls_loss (cur) = 0.421404, cls_loss (avg) = 0.461789, lr = 0.010000 | |
| iter = 548, accuracy (cur) = 0.880000 (all), 0.809524 (pos), 0.931034 (neg) | |
| iter = 548, accuracy (avg) = 0.777188 (all), 0.732625 (pos), 0.824672 (neg) | |
| data reader: epoch = 0, batch = 549 / 4040 | |
| iter = 549, cls_loss (cur) = 0.479861, cls_loss (avg) = 0.461970, lr = 0.010000 | |
| iter = 549, accuracy (cur) = 0.780000 (all), 0.862069 (pos), 0.666667 (neg) | |
| iter = 549, accuracy (avg) = 0.777216 (all), 0.733920 (pos), 0.823092 (neg) | |
| data reader: epoch = 0, batch = 550 / 4040 | |
| iter = 550, cls_loss (cur) = 0.496310, cls_loss (avg) = 0.462313, lr = 0.010000 | |
| iter = 550, accuracy (cur) = 0.740000 (all), 0.791667 (pos), 0.692308 (neg) | |
| iter = 550, accuracy (avg) = 0.776844 (all), 0.734497 (pos), 0.821784 (neg) | |
| data reader: epoch = 0, batch = 551 / 4040 | |
| iter = 551, cls_loss (cur) = 0.491138, cls_loss (avg) = 0.462602, lr = 0.010000 | |
| iter = 551, accuracy (cur) = 0.760000 (all), 0.739130 (pos), 0.777778 (neg) | |
| iter = 551, accuracy (avg) = 0.776675 (all), 0.734543 (pos), 0.821344 (neg) | |
| data reader: epoch = 0, batch = 552 / 4040 | |
| iter = 552, cls_loss (cur) = 0.557922, cls_loss (avg) = 0.463555, lr = 0.010000 | |
| iter = 552, accuracy (cur) = 0.720000 (all), 0.846154 (pos), 0.583333 (neg) | |
| iter = 552, accuracy (avg) = 0.776109 (all), 0.735659 (pos), 0.818964 (neg) | |
| data reader: epoch = 0, batch = 553 / 4040 | |
| iter = 553, cls_loss (cur) = 0.475773, cls_loss (avg) = 0.463677, lr = 0.010000 | |
| iter = 553, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.760000 (neg) | |
| iter = 553, accuracy (avg) = 0.776148 (all), 0.736303 (pos), 0.818374 (neg) | |
| data reader: epoch = 0, batch = 554 / 4040 | |
| iter = 554, cls_loss (cur) = 0.446468, cls_loss (avg) = 0.463505, lr = 0.010000 | |
| iter = 554, accuracy (cur) = 0.780000 (all), 0.681818 (pos), 0.857143 (neg) | |
| iter = 554, accuracy (avg) = 0.776186 (all), 0.735758 (pos), 0.818762 (neg) | |
| data reader: epoch = 0, batch = 555 / 4040 | |
| iter = 555, cls_loss (cur) = 0.375573, cls_loss (avg) = 0.462625, lr = 0.010000 | |
| iter = 555, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 555, accuracy (avg) = 0.776624 (all), 0.736862 (pos), 0.818491 (neg) | |
| data reader: epoch = 0, batch = 556 / 4040 | |
| iter = 556, cls_loss (cur) = 0.513134, cls_loss (avg) = 0.463131, lr = 0.010000 | |
| iter = 556, accuracy (cur) = 0.700000 (all), 0.761905 (pos), 0.655172 (neg) | |
| iter = 556, accuracy (avg) = 0.775858 (all), 0.737112 (pos), 0.816858 (neg) | |
| data reader: epoch = 0, batch = 557 / 4040 | |
| iter = 557, cls_loss (cur) = 0.457172, cls_loss (avg) = 0.463071, lr = 0.010000 | |
| iter = 557, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.833333 (neg) | |
| iter = 557, accuracy (avg) = 0.775899 (all), 0.737241 (pos), 0.817022 (neg) | |
| data reader: epoch = 0, batch = 558 / 4040 | |
| iter = 558, cls_loss (cur) = 0.452605, cls_loss (avg) = 0.462966, lr = 0.010000 | |
| iter = 558, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.807692 (neg) | |
| iter = 558, accuracy (avg) = 0.775940 (all), 0.737369 (pos), 0.816929 (neg) | |
| data reader: epoch = 0, batch = 559 / 4040 | |
| iter = 559, cls_loss (cur) = 0.378409, cls_loss (avg) = 0.462121, lr = 0.010000 | |
| iter = 559, accuracy (cur) = 0.860000 (all), 0.826087 (pos), 0.888889 (neg) | |
| iter = 559, accuracy (avg) = 0.776781 (all), 0.738256 (pos), 0.817649 (neg) | |
| data reader: epoch = 0, batch = 560 / 4040 | |
| iter = 560, cls_loss (cur) = 0.450657, cls_loss (avg) = 0.462006, lr = 0.010000 | |
| iter = 560, accuracy (cur) = 0.800000 (all), 0.722222 (pos), 0.843750 (neg) | |
| iter = 560, accuracy (avg) = 0.777013 (all), 0.738096 (pos), 0.817910 (neg) | |
| data reader: epoch = 0, batch = 561 / 4040 | |
| iter = 561, cls_loss (cur) = 0.400530, cls_loss (avg) = 0.461391, lr = 0.010000 | |
| iter = 561, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 561, accuracy (avg) = 0.776843 (all), 0.737115 (pos), 0.818531 (neg) | |
| data reader: epoch = 0, batch = 562 / 4040 | |
| iter = 562, cls_loss (cur) = 0.516668, cls_loss (avg) = 0.461944, lr = 0.010000 | |
| iter = 562, accuracy (cur) = 0.720000 (all), 0.571429 (pos), 0.827586 (neg) | |
| iter = 562, accuracy (avg) = 0.776275 (all), 0.735458 (pos), 0.818621 (neg) | |
| data reader: epoch = 0, batch = 563 / 4040 | |
| iter = 563, cls_loss (cur) = 0.385972, cls_loss (avg) = 0.461184, lr = 0.010000 | |
| iter = 563, accuracy (cur) = 0.820000 (all), 0.700000 (pos), 0.900000 (neg) | |
| iter = 563, accuracy (avg) = 0.776712 (all), 0.735103 (pos), 0.819435 (neg) | |
| data reader: epoch = 0, batch = 564 / 4040 | |
| iter = 564, cls_loss (cur) = 0.408830, cls_loss (avg) = 0.460661, lr = 0.010000 | |
| iter = 564, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.863636 (neg) | |
| iter = 564, accuracy (avg) = 0.776945 (all), 0.735252 (pos), 0.819877 (neg) | |
| data reader: epoch = 0, batch = 565 / 4040 | |
| iter = 565, cls_loss (cur) = 0.530513, cls_loss (avg) = 0.461359, lr = 0.010000 | |
| iter = 565, accuracy (cur) = 0.740000 (all), 0.571429 (pos), 0.862069 (neg) | |
| iter = 565, accuracy (avg) = 0.776575 (all), 0.733614 (pos), 0.820299 (neg) | |
| data reader: epoch = 0, batch = 566 / 4040 | |
| iter = 566, cls_loss (cur) = 0.460273, cls_loss (avg) = 0.461349, lr = 0.010000 | |
| iter = 566, accuracy (cur) = 0.820000 (all), 0.724138 (pos), 0.952381 (neg) | |
| iter = 566, accuracy (avg) = 0.777010 (all), 0.733519 (pos), 0.821620 (neg) | |
| data reader: epoch = 0, batch = 567 / 4040 | |
| iter = 567, cls_loss (cur) = 0.431033, cls_loss (avg) = 0.461045, lr = 0.010000 | |
| iter = 567, accuracy (cur) = 0.800000 (all), 0.680000 (pos), 0.920000 (neg) | |
| iter = 567, accuracy (avg) = 0.777239 (all), 0.732984 (pos), 0.822604 (neg) | |
| data reader: epoch = 0, batch = 568 / 4040 | |
| iter = 568, cls_loss (cur) = 0.451940, cls_loss (avg) = 0.460954, lr = 0.010000 | |
| iter = 568, accuracy (cur) = 0.780000 (all), 0.909091 (pos), 0.678571 (neg) | |
| iter = 568, accuracy (avg) = 0.777267 (all), 0.734745 (pos), 0.821163 (neg) | |
| data reader: epoch = 0, batch = 569 / 4040 | |
| iter = 569, cls_loss (cur) = 0.335602, cls_loss (avg) = 0.459701, lr = 0.010000 | |
| iter = 569, accuracy (cur) = 0.800000 (all), 0.913043 (pos), 0.703704 (neg) | |
| iter = 569, accuracy (avg) = 0.777494 (all), 0.736528 (pos), 0.819989 (neg) | |
| data reader: epoch = 0, batch = 570 / 4040 | |
| iter = 570, cls_loss (cur) = 0.312167, cls_loss (avg) = 0.458225, lr = 0.010000 | |
| iter = 570, accuracy (cur) = 0.920000 (all), 0.920000 (pos), 0.920000 (neg) | |
| iter = 570, accuracy (avg) = 0.778919 (all), 0.738363 (pos), 0.820989 (neg) | |
| data reader: epoch = 0, batch = 571 / 4040 | |
| iter = 571, cls_loss (cur) = 0.391176, cls_loss (avg) = 0.457555, lr = 0.010000 | |
| iter = 571, accuracy (cur) = 0.860000 (all), 0.840000 (pos), 0.880000 (neg) | |
| iter = 571, accuracy (avg) = 0.779730 (all), 0.739379 (pos), 0.821579 (neg) | |
| data reader: epoch = 0, batch = 572 / 4040 | |
| iter = 572, cls_loss (cur) = 0.360131, cls_loss (avg) = 0.456581, lr = 0.010000 | |
| iter = 572, accuracy (cur) = 0.840000 (all), 0.863636 (pos), 0.821429 (neg) | |
| iter = 572, accuracy (avg) = 0.780333 (all), 0.740622 (pos), 0.821577 (neg) | |
| data reader: epoch = 0, batch = 573 / 4040 | |
| iter = 573, cls_loss (cur) = 0.450716, cls_loss (avg) = 0.456522, lr = 0.010000 | |
| iter = 573, accuracy (cur) = 0.780000 (all), 0.733333 (pos), 0.850000 (neg) | |
| iter = 573, accuracy (avg) = 0.780330 (all), 0.740549 (pos), 0.821862 (neg) | |
| data reader: epoch = 0, batch = 574 / 4040 | |
| iter = 574, cls_loss (cur) = 0.448336, cls_loss (avg) = 0.456440, lr = 0.010000 | |
| iter = 574, accuracy (cur) = 0.800000 (all), 0.680000 (pos), 0.920000 (neg) | |
| iter = 574, accuracy (avg) = 0.780526 (all), 0.739943 (pos), 0.822843 (neg) | |
| data reader: epoch = 0, batch = 575 / 4040 | |
| iter = 575, cls_loss (cur) = 0.464437, cls_loss (avg) = 0.456520, lr = 0.010000 | |
| iter = 575, accuracy (cur) = 0.720000 (all), 0.739130 (pos), 0.703704 (neg) | |
| iter = 575, accuracy (avg) = 0.779921 (all), 0.739935 (pos), 0.821652 (neg) | |
| data reader: epoch = 0, batch = 576 / 4040 | |
| iter = 576, cls_loss (cur) = 0.304488, cls_loss (avg) = 0.455000, lr = 0.010000 | |
| iter = 576, accuracy (cur) = 0.900000 (all), 0.950000 (pos), 0.866667 (neg) | |
| iter = 576, accuracy (avg) = 0.781122 (all), 0.742036 (pos), 0.822102 (neg) | |
| data reader: epoch = 0, batch = 577 / 4040 | |
| iter = 577, cls_loss (cur) = 0.402783, cls_loss (avg) = 0.454478, lr = 0.010000 | |
| iter = 577, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 577, accuracy (avg) = 0.781111 (all), 0.741923 (pos), 0.822214 (neg) | |
| data reader: epoch = 0, batch = 578 / 4040 | |
| iter = 578, cls_loss (cur) = 0.400877, cls_loss (avg) = 0.453942, lr = 0.010000 | |
| iter = 578, accuracy (cur) = 0.800000 (all), 0.666667 (pos), 0.896552 (neg) | |
| iter = 578, accuracy (avg) = 0.781300 (all), 0.741171 (pos), 0.822957 (neg) | |
| data reader: epoch = 0, batch = 579 / 4040 | |
| iter = 579, cls_loss (cur) = 0.458914, cls_loss (avg) = 0.453991, lr = 0.010000 | |
| iter = 579, accuracy (cur) = 0.760000 (all), 0.692308 (pos), 0.833333 (neg) | |
| iter = 579, accuracy (avg) = 0.781087 (all), 0.740682 (pos), 0.823061 (neg) | |
| data reader: epoch = 0, batch = 580 / 4040 | |
| iter = 580, cls_loss (cur) = 0.516545, cls_loss (avg) = 0.454617, lr = 0.010000 | |
| iter = 580, accuracy (cur) = 0.680000 (all), 0.517241 (pos), 0.904762 (neg) | |
| iter = 580, accuracy (avg) = 0.780076 (all), 0.738448 (pos), 0.823878 (neg) | |
| data reader: epoch = 0, batch = 581 / 4040 | |
| iter = 581, cls_loss (cur) = 0.452882, cls_loss (avg) = 0.454600, lr = 0.010000 | |
| iter = 581, accuracy (cur) = 0.760000 (all), 0.708333 (pos), 0.807692 (neg) | |
| iter = 581, accuracy (avg) = 0.779875 (all), 0.738147 (pos), 0.823716 (neg) | |
| data reader: epoch = 0, batch = 582 / 4040 | |
| iter = 582, cls_loss (cur) = 0.478856, cls_loss (avg) = 0.454842, lr = 0.010000 | |
| iter = 582, accuracy (cur) = 0.720000 (all), 0.636364 (pos), 0.785714 (neg) | |
| iter = 582, accuracy (avg) = 0.779276 (all), 0.737129 (pos), 0.823336 (neg) | |
| data reader: epoch = 0, batch = 583 / 4040 | |
| iter = 583, cls_loss (cur) = 0.528087, cls_loss (avg) = 0.455575, lr = 0.010000 | |
| iter = 583, accuracy (cur) = 0.740000 (all), 0.904762 (pos), 0.620690 (neg) | |
| iter = 583, accuracy (avg) = 0.778883 (all), 0.738805 (pos), 0.821310 (neg) | |
| data reader: epoch = 0, batch = 584 / 4040 | |
| iter = 584, cls_loss (cur) = 0.557151, cls_loss (avg) = 0.456590, lr = 0.010000 | |
| iter = 584, accuracy (cur) = 0.780000 (all), 0.785714 (pos), 0.772727 (neg) | |
| iter = 584, accuracy (avg) = 0.778895 (all), 0.739274 (pos), 0.820824 (neg) | |
| data reader: epoch = 0, batch = 585 / 4040 | |
| iter = 585, cls_loss (cur) = 0.566795, cls_loss (avg) = 0.457692, lr = 0.010000 | |
| iter = 585, accuracy (cur) = 0.720000 (all), 0.913043 (pos), 0.555556 (neg) | |
| iter = 585, accuracy (avg) = 0.778306 (all), 0.741012 (pos), 0.818171 (neg) | |
| data reader: epoch = 0, batch = 586 / 4040 | |
| iter = 586, cls_loss (cur) = 0.431960, cls_loss (avg) = 0.457435, lr = 0.010000 | |
| iter = 586, accuracy (cur) = 0.800000 (all), 0.739130 (pos), 0.851852 (neg) | |
| iter = 586, accuracy (avg) = 0.778523 (all), 0.740993 (pos), 0.818508 (neg) | |
| data reader: epoch = 0, batch = 587 / 4040 | |
| iter = 587, cls_loss (cur) = 0.474586, cls_loss (avg) = 0.457607, lr = 0.010000 | |
| iter = 587, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.730769 (neg) | |
| iter = 587, accuracy (avg) = 0.778137 (all), 0.741083 (pos), 0.817631 (neg) | |
| data reader: epoch = 0, batch = 588 / 4040 | |
| iter = 588, cls_loss (cur) = 0.394950, cls_loss (avg) = 0.456980, lr = 0.010000 | |
| iter = 588, accuracy (cur) = 0.840000 (all), 0.666667 (pos), 1.000000 (neg) | |
| iter = 588, accuracy (avg) = 0.778756 (all), 0.740339 (pos), 0.819454 (neg) | |
| data reader: epoch = 0, batch = 589 / 4040 | |
| iter = 589, cls_loss (cur) = 0.522285, cls_loss (avg) = 0.457633, lr = 0.010000 | |
| iter = 589, accuracy (cur) = 0.760000 (all), 0.576923 (pos), 0.958333 (neg) | |
| iter = 589, accuracy (avg) = 0.778568 (all), 0.738705 (pos), 0.820843 (neg) | |
| data reader: epoch = 0, batch = 590 / 4040 | |
| iter = 590, cls_loss (cur) = 0.483629, cls_loss (avg) = 0.457893, lr = 0.010000 | |
| iter = 590, accuracy (cur) = 0.720000 (all), 0.702703 (pos), 0.769231 (neg) | |
| iter = 590, accuracy (avg) = 0.777983 (all), 0.738345 (pos), 0.820327 (neg) | |
| data reader: epoch = 0, batch = 591 / 4040 | |
| iter = 591, cls_loss (cur) = 0.392495, cls_loss (avg) = 0.457239, lr = 0.010000 | |
| iter = 591, accuracy (cur) = 0.860000 (all), 0.900000 (pos), 0.800000 (neg) | |
| iter = 591, accuracy (avg) = 0.778803 (all), 0.739961 (pos), 0.820124 (neg) | |
| data reader: epoch = 0, batch = 592 / 4040 | |
| iter = 592, cls_loss (cur) = 0.429955, cls_loss (avg) = 0.456966, lr = 0.010000 | |
| iter = 592, accuracy (cur) = 0.780000 (all), 0.785714 (pos), 0.772727 (neg) | |
| iter = 592, accuracy (avg) = 0.778815 (all), 0.740419 (pos), 0.819650 (neg) | |
| data reader: epoch = 0, batch = 593 / 4040 | |
| iter = 593, cls_loss (cur) = 0.369944, cls_loss (avg) = 0.456096, lr = 0.010000 | |
| iter = 593, accuracy (cur) = 0.860000 (all), 0.884615 (pos), 0.833333 (neg) | |
| iter = 593, accuracy (avg) = 0.779627 (all), 0.741861 (pos), 0.819787 (neg) | |
| data reader: epoch = 0, batch = 594 / 4040 | |
| iter = 594, cls_loss (cur) = 0.372488, cls_loss (avg) = 0.455260, lr = 0.010000 | |
| iter = 594, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 594, accuracy (avg) = 0.780630 (all), 0.742904 (pos), 0.820756 (neg) | |
| data reader: epoch = 0, batch = 595 / 4040 | |
| iter = 595, cls_loss (cur) = 0.334888, cls_loss (avg) = 0.454056, lr = 0.010000 | |
| iter = 595, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.888889 (neg) | |
| iter = 595, accuracy (avg) = 0.782224 (all), 0.745475 (pos), 0.821437 (neg) | |
| data reader: epoch = 0, batch = 596 / 4040 | |
| iter = 596, cls_loss (cur) = 0.454220, cls_loss (avg) = 0.454058, lr = 0.010000 | |
| iter = 596, accuracy (cur) = 0.800000 (all), 0.850000 (pos), 0.766667 (neg) | |
| iter = 596, accuracy (avg) = 0.782402 (all), 0.746520 (pos), 0.820889 (neg) | |
| data reader: epoch = 0, batch = 597 / 4040 | |
| iter = 597, cls_loss (cur) = 0.521066, cls_loss (avg) = 0.454728, lr = 0.010000 | |
| iter = 597, accuracy (cur) = 0.760000 (all), 0.826087 (pos), 0.703704 (neg) | |
| iter = 597, accuracy (avg) = 0.782178 (all), 0.747316 (pos), 0.819717 (neg) | |
| data reader: epoch = 0, batch = 598 / 4040 | |
| iter = 598, cls_loss (cur) = 0.387435, cls_loss (avg) = 0.454055, lr = 0.010000 | |
| iter = 598, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 598, accuracy (avg) = 0.782956 (all), 0.748463 (pos), 0.820092 (neg) | |
| data reader: epoch = 0, batch = 599 / 4040 | |
| iter = 599, cls_loss (cur) = 0.384426, cls_loss (avg) = 0.453359, lr = 0.010000 | |
| iter = 599, accuracy (cur) = 0.900000 (all), 0.840000 (pos), 0.960000 (neg) | |
| iter = 599, accuracy (avg) = 0.784127 (all), 0.749378 (pos), 0.821491 (neg) | |
| data reader: epoch = 0, batch = 600 / 4040 | |
| iter = 600, cls_loss (cur) = 0.435552, cls_loss (avg) = 0.453181, lr = 0.010000 | |
| iter = 600, accuracy (cur) = 0.820000 (all), 0.739130 (pos), 0.888889 (neg) | |
| iter = 600, accuracy (avg) = 0.784485 (all), 0.749276 (pos), 0.822165 (neg) | |
| data reader: epoch = 0, batch = 601 / 4040 | |
| iter = 601, cls_loss (cur) = 0.491388, cls_loss (avg) = 0.453563, lr = 0.010000 | |
| iter = 601, accuracy (cur) = 0.700000 (all), 0.666667 (pos), 0.730769 (neg) | |
| iter = 601, accuracy (avg) = 0.783640 (all), 0.748450 (pos), 0.821251 (neg) | |
| data reader: epoch = 0, batch = 602 / 4040 | |
| iter = 602, cls_loss (cur) = 0.430700, cls_loss (avg) = 0.453334, lr = 0.010000 | |
| iter = 602, accuracy (cur) = 0.820000 (all), 0.766667 (pos), 0.900000 (neg) | |
| iter = 602, accuracy (avg) = 0.784004 (all), 0.748632 (pos), 0.822038 (neg) | |
| data reader: epoch = 0, batch = 603 / 4040 | |
| iter = 603, cls_loss (cur) = 0.299576, cls_loss (avg) = 0.451796, lr = 0.010000 | |
| iter = 603, accuracy (cur) = 0.880000 (all), 0.791667 (pos), 0.961538 (neg) | |
| iter = 603, accuracy (avg) = 0.784964 (all), 0.749062 (pos), 0.823433 (neg) | |
| data reader: epoch = 0, batch = 604 / 4040 | |
| iter = 604, cls_loss (cur) = 0.448398, cls_loss (avg) = 0.451763, lr = 0.010000 | |
| iter = 604, accuracy (cur) = 0.820000 (all), 0.681818 (pos), 0.928571 (neg) | |
| iter = 604, accuracy (avg) = 0.785314 (all), 0.748390 (pos), 0.824485 (neg) | |
| data reader: epoch = 0, batch = 605 / 4040 | |
| iter = 605, cls_loss (cur) = 0.490710, cls_loss (avg) = 0.452152, lr = 0.010000 | |
| iter = 605, accuracy (cur) = 0.740000 (all), 0.633333 (pos), 0.900000 (neg) | |
| iter = 605, accuracy (avg) = 0.784861 (all), 0.747239 (pos), 0.825240 (neg) | |
| data reader: epoch = 0, batch = 606 / 4040 | |
| iter = 606, cls_loss (cur) = 0.382101, cls_loss (avg) = 0.451451, lr = 0.010000 | |
| iter = 606, accuracy (cur) = 0.840000 (all), 0.814815 (pos), 0.869565 (neg) | |
| iter = 606, accuracy (avg) = 0.785413 (all), 0.747915 (pos), 0.825683 (neg) | |
| data reader: epoch = 0, batch = 607 / 4040 | |
| iter = 607, cls_loss (cur) = 0.509186, cls_loss (avg) = 0.452029, lr = 0.010000 | |
| iter = 607, accuracy (cur) = 0.680000 (all), 0.851852 (pos), 0.478261 (neg) | |
| iter = 607, accuracy (avg) = 0.784358 (all), 0.748955 (pos), 0.822209 (neg) | |
| data reader: epoch = 0, batch = 608 / 4040 | |
| iter = 608, cls_loss (cur) = 0.377807, cls_loss (avg) = 0.451287, lr = 0.010000 | |
| iter = 608, accuracy (cur) = 0.860000 (all), 0.833333 (pos), 0.884615 (neg) | |
| iter = 608, accuracy (avg) = 0.785115 (all), 0.749798 (pos), 0.822833 (neg) | |
| data reader: epoch = 0, batch = 609 / 4040 | |
| iter = 609, cls_loss (cur) = 0.412760, cls_loss (avg) = 0.450901, lr = 0.010000 | |
| iter = 609, accuracy (cur) = 0.780000 (all), 0.739130 (pos), 0.814815 (neg) | |
| iter = 609, accuracy (avg) = 0.785064 (all), 0.749692 (pos), 0.822753 (neg) | |
| data reader: epoch = 0, batch = 610 / 4040 | |
| iter = 610, cls_loss (cur) = 0.403941, cls_loss (avg) = 0.450432, lr = 0.010000 | |
| iter = 610, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 610, accuracy (avg) = 0.785813 (all), 0.750272 (pos), 0.823692 (neg) | |
| data reader: epoch = 0, batch = 611 / 4040 | |
| iter = 611, cls_loss (cur) = 0.418093, cls_loss (avg) = 0.450108, lr = 0.010000 | |
| iter = 611, accuracy (cur) = 0.840000 (all), 0.925926 (pos), 0.739130 (neg) | |
| iter = 611, accuracy (avg) = 0.786355 (all), 0.752028 (pos), 0.822846 (neg) | |
| data reader: epoch = 0, batch = 612 / 4040 | |
| iter = 612, cls_loss (cur) = 0.383441, cls_loss (avg) = 0.449442, lr = 0.010000 | |
| iter = 612, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 612, accuracy (avg) = 0.786891 (all), 0.752508 (pos), 0.823284 (neg) | |
| data reader: epoch = 0, batch = 613 / 4040 | |
| iter = 613, cls_loss (cur) = 0.440288, cls_loss (avg) = 0.449350, lr = 0.010000 | |
| iter = 613, accuracy (cur) = 0.780000 (all), 0.791667 (pos), 0.769231 (neg) | |
| iter = 613, accuracy (avg) = 0.786823 (all), 0.752899 (pos), 0.822744 (neg) | |
| data reader: epoch = 0, batch = 614 / 4040 | |
| iter = 614, cls_loss (cur) = 0.454469, cls_loss (avg) = 0.449401, lr = 0.010000 | |
| iter = 614, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 614, accuracy (avg) = 0.787354 (all), 0.753770 (pos), 0.822916 (neg) | |
| data reader: epoch = 0, batch = 615 / 4040 | |
| iter = 615, cls_loss (cur) = 0.402737, cls_loss (avg) = 0.448935, lr = 0.010000 | |
| iter = 615, accuracy (cur) = 0.820000 (all), 0.880000 (pos), 0.760000 (neg) | |
| iter = 615, accuracy (avg) = 0.787681 (all), 0.755033 (pos), 0.822287 (neg) | |
| data reader: epoch = 0, batch = 616 / 4040 | |
| iter = 616, cls_loss (cur) = 0.449166, cls_loss (avg) = 0.448937, lr = 0.010000 | |
| iter = 616, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 616, accuracy (avg) = 0.787804 (all), 0.755482 (pos), 0.822064 (neg) | |
| data reader: epoch = 0, batch = 617 / 4040 | |
| iter = 617, cls_loss (cur) = 0.492841, cls_loss (avg) = 0.449376, lr = 0.010000 | |
| iter = 617, accuracy (cur) = 0.700000 (all), 0.476190 (pos), 0.862069 (neg) | |
| iter = 617, accuracy (avg) = 0.786926 (all), 0.752690 (pos), 0.822464 (neg) | |
| data reader: epoch = 0, batch = 618 / 4040 | |
| iter = 618, cls_loss (cur) = 0.323992, cls_loss (avg) = 0.448122, lr = 0.010000 | |
| iter = 618, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 618, accuracy (avg) = 0.788057 (all), 0.754052 (pos), 0.823370 (neg) | |
| data reader: epoch = 0, batch = 619 / 4040 | |
| iter = 619, cls_loss (cur) = 0.455739, cls_loss (avg) = 0.448198, lr = 0.010000 | |
| iter = 619, accuracy (cur) = 0.760000 (all), 0.684211 (pos), 0.806452 (neg) | |
| iter = 619, accuracy (avg) = 0.787776 (all), 0.753353 (pos), 0.823201 (neg) | |
| data reader: epoch = 0, batch = 620 / 4040 | |
| iter = 620, cls_loss (cur) = 0.291100, cls_loss (avg) = 0.446627, lr = 0.010000 | |
| iter = 620, accuracy (cur) = 0.900000 (all), 0.772727 (pos), 1.000000 (neg) | |
| iter = 620, accuracy (avg) = 0.788898 (all), 0.753547 (pos), 0.824969 (neg) | |
| data reader: epoch = 0, batch = 621 / 4040 | |
| iter = 621, cls_loss (cur) = 0.374102, cls_loss (avg) = 0.445902, lr = 0.010000 | |
| iter = 621, accuracy (cur) = 0.840000 (all), 0.760000 (pos), 0.920000 (neg) | |
| iter = 621, accuracy (avg) = 0.789409 (all), 0.753611 (pos), 0.825919 (neg) | |
| data reader: epoch = 0, batch = 622 / 4040 | |
| iter = 622, cls_loss (cur) = 0.328638, cls_loss (avg) = 0.444729, lr = 0.010000 | |
| iter = 622, accuracy (cur) = 0.880000 (all), 0.884615 (pos), 0.875000 (neg) | |
| iter = 622, accuracy (avg) = 0.790315 (all), 0.754921 (pos), 0.826410 (neg) | |
| data reader: epoch = 0, batch = 623 / 4040 | |
| iter = 623, cls_loss (cur) = 0.467414, cls_loss (avg) = 0.444956, lr = 0.010000 | |
| iter = 623, accuracy (cur) = 0.780000 (all), 0.840000 (pos), 0.720000 (neg) | |
| iter = 623, accuracy (avg) = 0.790212 (all), 0.755772 (pos), 0.825346 (neg) | |
| data reader: epoch = 0, batch = 624 / 4040 | |
| iter = 624, cls_loss (cur) = 0.427417, cls_loss (avg) = 0.444781, lr = 0.010000 | |
| iter = 624, accuracy (cur) = 0.760000 (all), 0.678571 (pos), 0.863636 (neg) | |
| iter = 624, accuracy (avg) = 0.789910 (all), 0.755000 (pos), 0.825729 (neg) | |
| data reader: epoch = 0, batch = 625 / 4040 | |
| iter = 625, cls_loss (cur) = 0.371288, cls_loss (avg) = 0.444046, lr = 0.010000 | |
| iter = 625, accuracy (cur) = 0.860000 (all), 0.827586 (pos), 0.904762 (neg) | |
| iter = 625, accuracy (avg) = 0.790611 (all), 0.755726 (pos), 0.826519 (neg) | |
| data reader: epoch = 0, batch = 626 / 4040 | |
| iter = 626, cls_loss (cur) = 0.442445, cls_loss (avg) = 0.444030, lr = 0.010000 | |
| iter = 626, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.857143 (neg) | |
| iter = 626, accuracy (avg) = 0.790505 (all), 0.755669 (pos), 0.826825 (neg) | |
| data reader: epoch = 0, batch = 627 / 4040 | |
| iter = 627, cls_loss (cur) = 0.379399, cls_loss (avg) = 0.443384, lr = 0.010000 | |
| iter = 627, accuracy (cur) = 0.860000 (all), 0.931034 (pos), 0.761905 (neg) | |
| iter = 627, accuracy (avg) = 0.791200 (all), 0.757422 (pos), 0.826176 (neg) | |
| data reader: epoch = 0, batch = 628 / 4040 | |
| iter = 628, cls_loss (cur) = 0.432041, cls_loss (avg) = 0.443270, lr = 0.010000 | |
| iter = 628, accuracy (cur) = 0.800000 (all), 1.000000 (pos), 0.642857 (neg) | |
| iter = 628, accuracy (avg) = 0.791288 (all), 0.759848 (pos), 0.824343 (neg) | |
| data reader: epoch = 0, batch = 629 / 4040 | |
| iter = 629, cls_loss (cur) = 0.346860, cls_loss (avg) = 0.442306, lr = 0.010000 | |
| iter = 629, accuracy (cur) = 0.860000 (all), 0.916667 (pos), 0.807692 (neg) | |
| iter = 629, accuracy (avg) = 0.791975 (all), 0.761416 (pos), 0.824177 (neg) | |
| data reader: epoch = 0, batch = 630 / 4040 | |
| iter = 630, cls_loss (cur) = 0.517340, cls_loss (avg) = 0.443056, lr = 0.010000 | |
| iter = 630, accuracy (cur) = 0.720000 (all), 0.720000 (pos), 0.720000 (neg) | |
| iter = 630, accuracy (avg) = 0.791255 (all), 0.761002 (pos), 0.823135 (neg) | |
| data reader: epoch = 0, batch = 631 / 4040 | |
| iter = 631, cls_loss (cur) = 0.386090, cls_loss (avg) = 0.442487, lr = 0.010000 | |
| iter = 631, accuracy (cur) = 0.880000 (all), 0.884615 (pos), 0.875000 (neg) | |
| iter = 631, accuracy (avg) = 0.792143 (all), 0.762238 (pos), 0.823653 (neg) | |
| data reader: epoch = 0, batch = 632 / 4040 | |
| iter = 632, cls_loss (cur) = 0.456775, cls_loss (avg) = 0.442630, lr = 0.010000 | |
| iter = 632, accuracy (cur) = 0.740000 (all), 0.709677 (pos), 0.789474 (neg) | |
| iter = 632, accuracy (avg) = 0.791621 (all), 0.761713 (pos), 0.823312 (neg) | |
| data reader: epoch = 0, batch = 633 / 4040 | |
| iter = 633, cls_loss (cur) = 0.454439, cls_loss (avg) = 0.442748, lr = 0.010000 | |
| iter = 633, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.730769 (neg) | |
| iter = 633, accuracy (avg) = 0.791105 (all), 0.761596 (pos), 0.822386 (neg) | |
| data reader: epoch = 0, batch = 634 / 4040 | |
| iter = 634, cls_loss (cur) = 0.441484, cls_loss (avg) = 0.442735, lr = 0.010000 | |
| iter = 634, accuracy (cur) = 0.760000 (all), 0.761905 (pos), 0.758621 (neg) | |
| iter = 634, accuracy (avg) = 0.790794 (all), 0.761599 (pos), 0.821749 (neg) | |
| data reader: epoch = 0, batch = 635 / 4040 | |
| iter = 635, cls_loss (cur) = 0.347007, cls_loss (avg) = 0.441778, lr = 0.010000 | |
| iter = 635, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.800000 (neg) | |
| iter = 635, accuracy (avg) = 0.791086 (all), 0.762316 (pos), 0.821531 (neg) | |
| data reader: epoch = 0, batch = 636 / 4040 | |
| iter = 636, cls_loss (cur) = 0.391553, cls_loss (avg) = 0.441276, lr = 0.010000 | |
| iter = 636, accuracy (cur) = 0.760000 (all), 0.760000 (pos), 0.760000 (neg) | |
| iter = 636, accuracy (avg) = 0.790775 (all), 0.762293 (pos), 0.820916 (neg) | |
| data reader: epoch = 0, batch = 637 / 4040 | |
| iter = 637, cls_loss (cur) = 0.447929, cls_loss (avg) = 0.441342, lr = 0.010000 | |
| iter = 637, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 637, accuracy (avg) = 0.790867 (all), 0.763070 (pos), 0.820307 (neg) | |
| data reader: epoch = 0, batch = 638 / 4040 | |
| iter = 638, cls_loss (cur) = 0.481971, cls_loss (avg) = 0.441748, lr = 0.010000 | |
| iter = 638, accuracy (cur) = 0.760000 (all), 0.761905 (pos), 0.758621 (neg) | |
| iter = 638, accuracy (avg) = 0.790559 (all), 0.763058 (pos), 0.819690 (neg) | |
| data reader: epoch = 0, batch = 639 / 4040 | |
| iter = 639, cls_loss (cur) = 0.459702, cls_loss (avg) = 0.441928, lr = 0.010000 | |
| iter = 639, accuracy (cur) = 0.800000 (all), 0.777778 (pos), 0.826087 (neg) | |
| iter = 639, accuracy (avg) = 0.790653 (all), 0.763206 (pos), 0.819754 (neg) | |
| data reader: epoch = 0, batch = 640 / 4040 | |
| iter = 640, cls_loss (cur) = 0.447784, cls_loss (avg) = 0.441987, lr = 0.010000 | |
| iter = 640, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 640, accuracy (avg) = 0.790347 (all), 0.761973 (pos), 0.820356 (neg) | |
| data reader: epoch = 0, batch = 641 / 4040 | |
| iter = 641, cls_loss (cur) = 0.459828, cls_loss (avg) = 0.442165, lr = 0.010000 | |
| iter = 641, accuracy (cur) = 0.760000 (all), 0.727273 (pos), 0.785714 (neg) | |
| iter = 641, accuracy (avg) = 0.790043 (all), 0.761626 (pos), 0.820010 (neg) | |
| data reader: epoch = 0, batch = 642 / 4040 | |
| iter = 642, cls_loss (cur) = 0.397255, cls_loss (avg) = 0.441716, lr = 0.010000 | |
| iter = 642, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 642, accuracy (avg) = 0.790343 (all), 0.761610 (pos), 0.820610 (neg) | |
| data reader: epoch = 0, batch = 643 / 4040 | |
| iter = 643, cls_loss (cur) = 0.399523, cls_loss (avg) = 0.441294, lr = 0.010000 | |
| iter = 643, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 643, accuracy (avg) = 0.790839 (all), 0.762327 (pos), 0.820865 (neg) | |
| data reader: epoch = 0, batch = 644 / 4040 | |
| iter = 644, cls_loss (cur) = 0.372224, cls_loss (avg) = 0.440603, lr = 0.010000 | |
| iter = 644, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 644, accuracy (avg) = 0.791131 (all), 0.762621 (pos), 0.821118 (neg) | |
| data reader: epoch = 0, batch = 645 / 4040 | |
| iter = 645, cls_loss (cur) = 0.454490, cls_loss (avg) = 0.440742, lr = 0.010000 | |
| iter = 645, accuracy (cur) = 0.800000 (all), 0.769231 (pos), 0.833333 (neg) | |
| iter = 645, accuracy (avg) = 0.791219 (all), 0.762687 (pos), 0.821240 (neg) | |
| data reader: epoch = 0, batch = 646 / 4040 | |
| iter = 646, cls_loss (cur) = 0.464325, cls_loss (avg) = 0.440978, lr = 0.010000 | |
| iter = 646, accuracy (cur) = 0.780000 (all), 0.807692 (pos), 0.750000 (neg) | |
| iter = 646, accuracy (avg) = 0.791107 (all), 0.763137 (pos), 0.820528 (neg) | |
| data reader: epoch = 0, batch = 647 / 4040 | |
| iter = 647, cls_loss (cur) = 0.317423, cls_loss (avg) = 0.439742, lr = 0.010000 | |
| iter = 647, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 647, accuracy (avg) = 0.792196 (all), 0.764736 (pos), 0.821072 (neg) | |
| data reader: epoch = 0, batch = 648 / 4040 | |
| iter = 648, cls_loss (cur) = 0.411048, cls_loss (avg) = 0.439455, lr = 0.010000 | |
| iter = 648, accuracy (cur) = 0.780000 (all), 0.952381 (pos), 0.655172 (neg) | |
| iter = 648, accuracy (avg) = 0.792074 (all), 0.766613 (pos), 0.819413 (neg) | |
| data reader: epoch = 0, batch = 649 / 4040 | |
| iter = 649, cls_loss (cur) = 0.316311, cls_loss (avg) = 0.438224, lr = 0.010000 | |
| iter = 649, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 649, accuracy (avg) = 0.792954 (all), 0.767583 (pos), 0.820148 (neg) | |
| data reader: epoch = 0, batch = 650 / 4040 | |
| iter = 650, cls_loss (cur) = 0.476981, cls_loss (avg) = 0.438612, lr = 0.010000 | |
| iter = 650, accuracy (cur) = 0.780000 (all), 0.760000 (pos), 0.800000 (neg) | |
| iter = 650, accuracy (avg) = 0.792824 (all), 0.767507 (pos), 0.819946 (neg) | |
| data reader: epoch = 0, batch = 651 / 4040 | |
| iter = 651, cls_loss (cur) = 0.499254, cls_loss (avg) = 0.439218, lr = 0.010000 | |
| iter = 651, accuracy (cur) = 0.760000 (all), 0.714286 (pos), 0.818182 (neg) | |
| iter = 651, accuracy (avg) = 0.792496 (all), 0.766975 (pos), 0.819929 (neg) | |
| data reader: epoch = 0, batch = 652 / 4040 | |
| iter = 652, cls_loss (cur) = 0.339006, cls_loss (avg) = 0.438216, lr = 0.010000 | |
| iter = 652, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 652, accuracy (avg) = 0.793371 (all), 0.767705 (pos), 0.820930 (neg) | |
| data reader: epoch = 0, batch = 653 / 4040 | |
| iter = 653, cls_loss (cur) = 0.441022, cls_loss (avg) = 0.438244, lr = 0.010000 | |
| iter = 653, accuracy (cur) = 0.820000 (all), 0.863636 (pos), 0.785714 (neg) | |
| iter = 653, accuracy (avg) = 0.793637 (all), 0.768665 (pos), 0.820577 (neg) | |
| data reader: epoch = 0, batch = 654 / 4040 | |
| iter = 654, cls_loss (cur) = 0.430832, cls_loss (avg) = 0.438170, lr = 0.010000 | |
| iter = 654, accuracy (cur) = 0.860000 (all), 0.913043 (pos), 0.814815 (neg) | |
| iter = 654, accuracy (avg) = 0.794301 (all), 0.770108 (pos), 0.820520 (neg) | |
| data reader: epoch = 0, batch = 655 / 4040 | |
| iter = 655, cls_loss (cur) = 0.442498, cls_loss (avg) = 0.438213, lr = 0.010000 | |
| iter = 655, accuracy (cur) = 0.780000 (all), 0.684211 (pos), 0.838710 (neg) | |
| iter = 655, accuracy (avg) = 0.794158 (all), 0.769249 (pos), 0.820702 (neg) | |
| data reader: epoch = 0, batch = 656 / 4040 | |
| iter = 656, cls_loss (cur) = 0.400929, cls_loss (avg) = 0.437840, lr = 0.010000 | |
| iter = 656, accuracy (cur) = 0.840000 (all), 0.680000 (pos), 1.000000 (neg) | |
| iter = 656, accuracy (avg) = 0.794616 (all), 0.768357 (pos), 0.822495 (neg) | |
| data reader: epoch = 0, batch = 657 / 4040 | |
| iter = 657, cls_loss (cur) = 0.530916, cls_loss (avg) = 0.438771, lr = 0.010000 | |
| iter = 657, accuracy (cur) = 0.720000 (all), 0.608696 (pos), 0.814815 (neg) | |
| iter = 657, accuracy (avg) = 0.793870 (all), 0.766760 (pos), 0.822418 (neg) | |
| data reader: epoch = 0, batch = 658 / 4040 | |
| iter = 658, cls_loss (cur) = 0.433011, cls_loss (avg) = 0.438713, lr = 0.010000 | |
| iter = 658, accuracy (cur) = 0.820000 (all), 0.888889 (pos), 0.739130 (neg) | |
| iter = 658, accuracy (avg) = 0.794131 (all), 0.767982 (pos), 0.821585 (neg) | |
| data reader: epoch = 0, batch = 659 / 4040 | |
| iter = 659, cls_loss (cur) = 0.410097, cls_loss (avg) = 0.438427, lr = 0.010000 | |
| iter = 659, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 659, accuracy (avg) = 0.794190 (all), 0.768302 (pos), 0.821369 (neg) | |
| data reader: epoch = 0, batch = 660 / 4040 | |
| iter = 660, cls_loss (cur) = 0.361807, cls_loss (avg) = 0.437661, lr = 0.010000 | |
| iter = 660, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.875000 (neg) | |
| iter = 660, accuracy (avg) = 0.795048 (all), 0.769508 (pos), 0.821905 (neg) | |
| data reader: epoch = 0, batch = 661 / 4040 | |
| iter = 661, cls_loss (cur) = 0.406117, cls_loss (avg) = 0.437346, lr = 0.010000 | |
| iter = 661, accuracy (cur) = 0.800000 (all), 0.740741 (pos), 0.869565 (neg) | |
| iter = 661, accuracy (avg) = 0.795098 (all), 0.769220 (pos), 0.822382 (neg) | |
| data reader: epoch = 0, batch = 662 / 4040 | |
| iter = 662, cls_loss (cur) = 0.393782, cls_loss (avg) = 0.436910, lr = 0.010000 | |
| iter = 662, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 662, accuracy (avg) = 0.795747 (all), 0.770148 (pos), 0.822730 (neg) | |
| data reader: epoch = 0, batch = 663 / 4040 | |
| iter = 663, cls_loss (cur) = 0.383343, cls_loss (avg) = 0.436374, lr = 0.010000 | |
| iter = 663, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 663, accuracy (avg) = 0.796189 (all), 0.770909 (pos), 0.822836 (neg) | |
| data reader: epoch = 0, batch = 664 / 4040 | |
| iter = 664, cls_loss (cur) = 0.374773, cls_loss (avg) = 0.435758, lr = 0.010000 | |
| iter = 664, accuracy (cur) = 0.860000 (all), 0.896552 (pos), 0.809524 (neg) | |
| iter = 664, accuracy (avg) = 0.796827 (all), 0.772165 (pos), 0.822703 (neg) | |
| data reader: epoch = 0, batch = 665 / 4040 | |
| iter = 665, cls_loss (cur) = 0.438196, cls_loss (avg) = 0.435783, lr = 0.010000 | |
| iter = 665, accuracy (cur) = 0.820000 (all), 0.787879 (pos), 0.882353 (neg) | |
| iter = 665, accuracy (avg) = 0.797059 (all), 0.772322 (pos), 0.823299 (neg) | |
| data reader: epoch = 0, batch = 666 / 4040 | |
| iter = 666, cls_loss (cur) = 0.413587, cls_loss (avg) = 0.435561, lr = 0.010000 | |
| iter = 666, accuracy (cur) = 0.840000 (all), 0.850000 (pos), 0.833333 (neg) | |
| iter = 666, accuracy (avg) = 0.797488 (all), 0.773099 (pos), 0.823399 (neg) | |
| data reader: epoch = 0, batch = 667 / 4040 | |
| iter = 667, cls_loss (cur) = 0.330629, cls_loss (avg) = 0.434511, lr = 0.010000 | |
| iter = 667, accuracy (cur) = 0.860000 (all), 0.870968 (pos), 0.842105 (neg) | |
| iter = 667, accuracy (avg) = 0.798113 (all), 0.774078 (pos), 0.823586 (neg) | |
| data reader: epoch = 0, batch = 668 / 4040 | |
| iter = 668, cls_loss (cur) = 0.357165, cls_loss (avg) = 0.433738, lr = 0.010000 | |
| iter = 668, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.857143 (neg) | |
| iter = 668, accuracy (avg) = 0.798932 (all), 0.775428 (pos), 0.823922 (neg) | |
| data reader: epoch = 0, batch = 669 / 4040 | |
| iter = 669, cls_loss (cur) = 0.475551, cls_loss (avg) = 0.434156, lr = 0.010000 | |
| iter = 669, accuracy (cur) = 0.700000 (all), 0.760000 (pos), 0.640000 (neg) | |
| iter = 669, accuracy (avg) = 0.797943 (all), 0.775273 (pos), 0.822083 (neg) | |
| data reader: epoch = 0, batch = 670 / 4040 | |
| iter = 670, cls_loss (cur) = 0.438682, cls_loss (avg) = 0.434201, lr = 0.010000 | |
| iter = 670, accuracy (cur) = 0.820000 (all), 0.842105 (pos), 0.806452 (neg) | |
| iter = 670, accuracy (avg) = 0.798164 (all), 0.775942 (pos), 0.821926 (neg) | |
| data reader: epoch = 0, batch = 671 / 4040 | |
| iter = 671, cls_loss (cur) = 0.435916, cls_loss (avg) = 0.434218, lr = 0.010000 | |
| iter = 671, accuracy (cur) = 0.860000 (all), 0.909091 (pos), 0.821429 (neg) | |
| iter = 671, accuracy (avg) = 0.798782 (all), 0.777273 (pos), 0.821921 (neg) | |
| data reader: epoch = 0, batch = 672 / 4040 | |
| iter = 672, cls_loss (cur) = 0.444960, cls_loss (avg) = 0.434326, lr = 0.010000 | |
| iter = 672, accuracy (cur) = 0.820000 (all), 0.793103 (pos), 0.857143 (neg) | |
| iter = 672, accuracy (avg) = 0.798994 (all), 0.777432 (pos), 0.822274 (neg) | |
| data reader: epoch = 0, batch = 673 / 4040 | |
| iter = 673, cls_loss (cur) = 0.434677, cls_loss (avg) = 0.434329, lr = 0.010000 | |
| iter = 673, accuracy (cur) = 0.800000 (all), 0.857143 (pos), 0.758621 (neg) | |
| iter = 673, accuracy (avg) = 0.799004 (all), 0.778229 (pos), 0.821637 (neg) | |
| data reader: epoch = 0, batch = 674 / 4040 | |
| iter = 674, cls_loss (cur) = 0.383408, cls_loss (avg) = 0.433820, lr = 0.010000 | |
| iter = 674, accuracy (cur) = 0.880000 (all), 0.869565 (pos), 0.888889 (neg) | |
| iter = 674, accuracy (avg) = 0.799814 (all), 0.779142 (pos), 0.822310 (neg) | |
| data reader: epoch = 0, batch = 675 / 4040 | |
| iter = 675, cls_loss (cur) = 0.505748, cls_loss (avg) = 0.434539, lr = 0.010000 | |
| iter = 675, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 675, accuracy (avg) = 0.799416 (all), 0.778388 (pos), 0.822347 (neg) | |
| data reader: epoch = 0, batch = 676 / 4040 | |
| iter = 676, cls_loss (cur) = 0.362102, cls_loss (avg) = 0.433815, lr = 0.010000 | |
| iter = 676, accuracy (cur) = 0.840000 (all), 0.739130 (pos), 0.925926 (neg) | |
| iter = 676, accuracy (avg) = 0.799822 (all), 0.777995 (pos), 0.823383 (neg) | |
| data reader: epoch = 0, batch = 677 / 4040 | |
| iter = 677, cls_loss (cur) = 0.436179, cls_loss (avg) = 0.433839, lr = 0.010000 | |
| iter = 677, accuracy (cur) = 0.820000 (all), 0.720000 (pos), 0.920000 (neg) | |
| iter = 677, accuracy (avg) = 0.800024 (all), 0.777415 (pos), 0.824349 (neg) | |
| data reader: epoch = 0, batch = 678 / 4040 | |
| iter = 678, cls_loss (cur) = 0.367575, cls_loss (avg) = 0.433176, lr = 0.010000 | |
| iter = 678, accuracy (cur) = 0.880000 (all), 0.925926 (pos), 0.826087 (neg) | |
| iter = 678, accuracy (avg) = 0.800823 (all), 0.778900 (pos), 0.824367 (neg) | |
| data reader: epoch = 0, batch = 679 / 4040 | |
| iter = 679, cls_loss (cur) = 0.393133, cls_loss (avg) = 0.432776, lr = 0.010000 | |
| iter = 679, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 679, accuracy (avg) = 0.800815 (all), 0.779293 (pos), 0.823980 (neg) | |
| data reader: epoch = 0, batch = 680 / 4040 | |
| iter = 680, cls_loss (cur) = 0.440782, cls_loss (avg) = 0.432856, lr = 0.010000 | |
| iter = 680, accuracy (cur) = 0.780000 (all), 0.769231 (pos), 0.791667 (neg) | |
| iter = 680, accuracy (avg) = 0.800607 (all), 0.779192 (pos), 0.823657 (neg) | |
| data reader: epoch = 0, batch = 681 / 4040 | |
| iter = 681, cls_loss (cur) = 0.408014, cls_loss (avg) = 0.432607, lr = 0.010000 | |
| iter = 681, accuracy (cur) = 0.820000 (all), 0.892857 (pos), 0.727273 (neg) | |
| iter = 681, accuracy (avg) = 0.800801 (all), 0.780329 (pos), 0.822693 (neg) | |
| data reader: epoch = 0, batch = 682 / 4040 | |
| iter = 682, cls_loss (cur) = 0.351522, cls_loss (avg) = 0.431796, lr = 0.010000 | |
| iter = 682, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 682, accuracy (avg) = 0.801393 (all), 0.780603 (pos), 0.823633 (neg) | |
| data reader: epoch = 0, batch = 683 / 4040 | |
| iter = 683, cls_loss (cur) = 0.455830, cls_loss (avg) = 0.432037, lr = 0.010000 | |
| iter = 683, accuracy (cur) = 0.800000 (all), 0.875000 (pos), 0.764706 (neg) | |
| iter = 683, accuracy (avg) = 0.801379 (all), 0.781547 (pos), 0.823044 (neg) | |
| data reader: epoch = 0, batch = 684 / 4040 | |
| iter = 684, cls_loss (cur) = 0.327231, cls_loss (avg) = 0.430989, lr = 0.010000 | |
| iter = 684, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 684, accuracy (avg) = 0.801965 (all), 0.781808 (pos), 0.823980 (neg) | |
| data reader: epoch = 0, batch = 685 / 4040 | |
| iter = 685, cls_loss (cur) = 0.390066, cls_loss (avg) = 0.430579, lr = 0.010000 | |
| iter = 685, accuracy (cur) = 0.840000 (all), 0.666667 (pos), 0.965517 (neg) | |
| iter = 685, accuracy (avg) = 0.802346 (all), 0.780657 (pos), 0.825395 (neg) | |
| data reader: epoch = 0, batch = 686 / 4040 | |
| iter = 686, cls_loss (cur) = 0.393230, cls_loss (avg) = 0.430206, lr = 0.010000 | |
| iter = 686, accuracy (cur) = 0.780000 (all), 0.714286 (pos), 0.827586 (neg) | |
| iter = 686, accuracy (avg) = 0.802122 (all), 0.779993 (pos), 0.825417 (neg) | |
| data reader: epoch = 0, batch = 687 / 4040 | |
| iter = 687, cls_loss (cur) = 0.423224, cls_loss (avg) = 0.430136, lr = 0.010000 | |
| iter = 687, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.923077 (neg) | |
| iter = 687, accuracy (avg) = 0.802501 (all), 0.779693 (pos), 0.826394 (neg) | |
| data reader: epoch = 0, batch = 688 / 4040 | |
| iter = 688, cls_loss (cur) = 0.519898, cls_loss (avg) = 0.431034, lr = 0.010000 | |
| iter = 688, accuracy (cur) = 0.740000 (all), 0.760000 (pos), 0.720000 (neg) | |
| iter = 688, accuracy (avg) = 0.801876 (all), 0.779496 (pos), 0.825330 (neg) | |
| data reader: epoch = 0, batch = 689 / 4040 | |
| iter = 689, cls_loss (cur) = 0.463546, cls_loss (avg) = 0.431359, lr = 0.010000 | |
| iter = 689, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.714286 (neg) | |
| iter = 689, accuracy (avg) = 0.801457 (all), 0.779883 (pos), 0.824219 (neg) | |
| data reader: epoch = 0, batch = 690 / 4040 | |
| iter = 690, cls_loss (cur) = 0.436260, cls_loss (avg) = 0.431408, lr = 0.010000 | |
| iter = 690, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 690, accuracy (avg) = 0.801843 (all), 0.780161 (pos), 0.824727 (neg) | |
| data reader: epoch = 0, batch = 691 / 4040 | |
| iter = 691, cls_loss (cur) = 0.374666, cls_loss (avg) = 0.430841, lr = 0.010000 | |
| iter = 691, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.840000 (neg) | |
| iter = 691, accuracy (avg) = 0.802024 (all), 0.780359 (pos), 0.824880 (neg) | |
| data reader: epoch = 0, batch = 692 / 4040 | |
| iter = 692, cls_loss (cur) = 0.437204, cls_loss (avg) = 0.430904, lr = 0.010000 | |
| iter = 692, accuracy (cur) = 0.780000 (all), 0.851852 (pos), 0.695652 (neg) | |
| iter = 692, accuracy (avg) = 0.801804 (all), 0.781074 (pos), 0.823588 (neg) | |
| data reader: epoch = 0, batch = 693 / 4040 | |
| iter = 693, cls_loss (cur) = 0.386847, cls_loss (avg) = 0.430464, lr = 0.010000 | |
| iter = 693, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.846154 (neg) | |
| iter = 693, accuracy (avg) = 0.801786 (all), 0.780764 (pos), 0.823813 (neg) | |
| data reader: epoch = 0, batch = 694 / 4040 | |
| iter = 694, cls_loss (cur) = 0.451682, cls_loss (avg) = 0.430676, lr = 0.010000 | |
| iter = 694, accuracy (cur) = 0.800000 (all), 0.724138 (pos), 0.904762 (neg) | |
| iter = 694, accuracy (avg) = 0.801768 (all), 0.780197 (pos), 0.824623 (neg) | |
| data reader: epoch = 0, batch = 695 / 4040 | |
| iter = 695, cls_loss (cur) = 0.503794, cls_loss (avg) = 0.431407, lr = 0.010000 | |
| iter = 695, accuracy (cur) = 0.800000 (all), 0.793103 (pos), 0.809524 (neg) | |
| iter = 695, accuracy (avg) = 0.801750 (all), 0.780326 (pos), 0.824472 (neg) | |
| data reader: epoch = 0, batch = 696 / 4040 | |
| iter = 696, cls_loss (cur) = 0.469892, cls_loss (avg) = 0.431792, lr = 0.010000 | |
| iter = 696, accuracy (cur) = 0.740000 (all), 0.840000 (pos), 0.640000 (neg) | |
| iter = 696, accuracy (avg) = 0.801133 (all), 0.780923 (pos), 0.822627 (neg) | |
| data reader: epoch = 0, batch = 697 / 4040 | |
| iter = 697, cls_loss (cur) = 0.325254, cls_loss (avg) = 0.430726, lr = 0.010000 | |
| iter = 697, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 697, accuracy (avg) = 0.802121 (all), 0.782003 (pos), 0.823531 (neg) | |
| data reader: epoch = 0, batch = 698 / 4040 | |
| iter = 698, cls_loss (cur) = 0.407663, cls_loss (avg) = 0.430496, lr = 0.010000 | |
| iter = 698, accuracy (cur) = 0.860000 (all), 0.931034 (pos), 0.761905 (neg) | |
| iter = 698, accuracy (avg) = 0.802700 (all), 0.783493 (pos), 0.822915 (neg) | |
| data reader: epoch = 0, batch = 699 / 4040 | |
| iter = 699, cls_loss (cur) = 0.370838, cls_loss (avg) = 0.429899, lr = 0.010000 | |
| iter = 699, accuracy (cur) = 0.900000 (all), 0.952381 (pos), 0.862069 (neg) | |
| iter = 699, accuracy (avg) = 0.803673 (all), 0.785182 (pos), 0.823307 (neg) | |
| data reader: epoch = 0, batch = 700 / 4040 | |
| iter = 700, cls_loss (cur) = 0.413436, cls_loss (avg) = 0.429735, lr = 0.010000 | |
| iter = 700, accuracy (cur) = 0.780000 (all), 0.758621 (pos), 0.809524 (neg) | |
| iter = 700, accuracy (avg) = 0.803437 (all), 0.784916 (pos), 0.823169 (neg) | |
| data reader: epoch = 0, batch = 701 / 4040 | |
| iter = 701, cls_loss (cur) = 0.430845, cls_loss (avg) = 0.429746, lr = 0.010000 | |
| iter = 701, accuracy (cur) = 0.780000 (all), 0.692308 (pos), 0.875000 (neg) | |
| iter = 701, accuracy (avg) = 0.803202 (all), 0.783990 (pos), 0.823687 (neg) | |
| data reader: epoch = 0, batch = 702 / 4040 | |
| iter = 702, cls_loss (cur) = 0.502118, cls_loss (avg) = 0.430469, lr = 0.010000 | |
| iter = 702, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.727273 (neg) | |
| iter = 702, accuracy (avg) = 0.802570 (all), 0.783650 (pos), 0.822723 (neg) | |
| data reader: epoch = 0, batch = 703 / 4040 | |
| iter = 703, cls_loss (cur) = 0.457884, cls_loss (avg) = 0.430744, lr = 0.010000 | |
| iter = 703, accuracy (cur) = 0.780000 (all), 0.821429 (pos), 0.727273 (neg) | |
| iter = 703, accuracy (avg) = 0.802344 (all), 0.784028 (pos), 0.821768 (neg) | |
| data reader: epoch = 0, batch = 704 / 4040 | |
| iter = 704, cls_loss (cur) = 0.469821, cls_loss (avg) = 0.431134, lr = 0.010000 | |
| iter = 704, accuracy (cur) = 0.680000 (all), 0.724138 (pos), 0.619048 (neg) | |
| iter = 704, accuracy (avg) = 0.801121 (all), 0.783429 (pos), 0.819741 (neg) | |
| data reader: epoch = 0, batch = 705 / 4040 | |
| iter = 705, cls_loss (cur) = 0.404867, cls_loss (avg) = 0.430872, lr = 0.010000 | |
| iter = 705, accuracy (cur) = 0.840000 (all), 0.842105 (pos), 0.838710 (neg) | |
| iter = 705, accuracy (avg) = 0.801510 (all), 0.784016 (pos), 0.819931 (neg) | |
| data reader: epoch = 0, batch = 706 / 4040 | |
| iter = 706, cls_loss (cur) = 0.399616, cls_loss (avg) = 0.430559, lr = 0.010000 | |
| iter = 706, accuracy (cur) = 0.860000 (all), 0.760000 (pos), 0.960000 (neg) | |
| iter = 706, accuracy (avg) = 0.802095 (all), 0.783776 (pos), 0.821332 (neg) | |
| data reader: epoch = 0, batch = 707 / 4040 | |
| iter = 707, cls_loss (cur) = 0.396158, cls_loss (avg) = 0.430215, lr = 0.010000 | |
| iter = 707, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 707, accuracy (avg) = 0.802274 (all), 0.783630 (pos), 0.821868 (neg) | |
| data reader: epoch = 0, batch = 708 / 4040 | |
| iter = 708, cls_loss (cur) = 0.469571, cls_loss (avg) = 0.430609, lr = 0.010000 | |
| iter = 708, accuracy (cur) = 0.740000 (all), 0.863636 (pos), 0.642857 (neg) | |
| iter = 708, accuracy (avg) = 0.801651 (all), 0.784431 (pos), 0.820078 (neg) | |
| data reader: epoch = 0, batch = 709 / 4040 | |
| iter = 709, cls_loss (cur) = 0.525625, cls_loss (avg) = 0.431559, lr = 0.010000 | |
| iter = 709, accuracy (cur) = 0.700000 (all), 0.709677 (pos), 0.684211 (neg) | |
| iter = 709, accuracy (avg) = 0.800634 (all), 0.783683 (pos), 0.818720 (neg) | |
| data reader: epoch = 0, batch = 710 / 4040 | |
| iter = 710, cls_loss (cur) = 0.431345, cls_loss (avg) = 0.431557, lr = 0.010000 | |
| iter = 710, accuracy (cur) = 0.800000 (all), 0.880000 (pos), 0.720000 (neg) | |
| iter = 710, accuracy (avg) = 0.800628 (all), 0.784646 (pos), 0.817732 (neg) | |
| data reader: epoch = 0, batch = 711 / 4040 | |
| iter = 711, cls_loss (cur) = 0.461330, cls_loss (avg) = 0.431854, lr = 0.010000 | |
| iter = 711, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 711, accuracy (avg) = 0.800822 (all), 0.784716 (pos), 0.818017 (neg) | |
| data reader: epoch = 0, batch = 712 / 4040 | |
| iter = 712, cls_loss (cur) = 0.415231, cls_loss (avg) = 0.431688, lr = 0.010000 | |
| iter = 712, accuracy (cur) = 0.740000 (all), 0.777778 (pos), 0.695652 (neg) | |
| iter = 712, accuracy (avg) = 0.800214 (all), 0.784647 (pos), 0.816793 (neg) | |
| data reader: epoch = 0, batch = 713 / 4040 | |
| iter = 713, cls_loss (cur) = 0.418563, cls_loss (avg) = 0.431557, lr = 0.010000 | |
| iter = 713, accuracy (cur) = 0.820000 (all), 0.950000 (pos), 0.733333 (neg) | |
| iter = 713, accuracy (avg) = 0.800412 (all), 0.786301 (pos), 0.815958 (neg) | |
| data reader: epoch = 0, batch = 714 / 4040 | |
| iter = 714, cls_loss (cur) = 0.393708, cls_loss (avg) = 0.431178, lr = 0.010000 | |
| iter = 714, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 714, accuracy (avg) = 0.801007 (all), 0.787187 (pos), 0.816260 (neg) | |
| data reader: epoch = 0, batch = 715 / 4040 | |
| iter = 715, cls_loss (cur) = 0.338501, cls_loss (avg) = 0.430252, lr = 0.010000 | |
| iter = 715, accuracy (cur) = 0.880000 (all), 0.947368 (pos), 0.838710 (neg) | |
| iter = 715, accuracy (avg) = 0.801797 (all), 0.788789 (pos), 0.816485 (neg) | |
| data reader: epoch = 0, batch = 716 / 4040 | |
| iter = 716, cls_loss (cur) = 0.437477, cls_loss (avg) = 0.430324, lr = 0.010000 | |
| iter = 716, accuracy (cur) = 0.760000 (all), 0.636364 (pos), 0.857143 (neg) | |
| iter = 716, accuracy (avg) = 0.801379 (all), 0.787265 (pos), 0.816891 (neg) | |
| data reader: epoch = 0, batch = 717 / 4040 | |
| iter = 717, cls_loss (cur) = 0.369289, cls_loss (avg) = 0.429714, lr = 0.010000 | |
| iter = 717, accuracy (cur) = 0.860000 (all), 0.833333 (pos), 0.900000 (neg) | |
| iter = 717, accuracy (avg) = 0.801966 (all), 0.787726 (pos), 0.817722 (neg) | |
| data reader: epoch = 0, batch = 718 / 4040 | |
| iter = 718, cls_loss (cur) = 0.469500, cls_loss (avg) = 0.430111, lr = 0.010000 | |
| iter = 718, accuracy (cur) = 0.760000 (all), 0.695652 (pos), 0.814815 (neg) | |
| iter = 718, accuracy (avg) = 0.801546 (all), 0.786805 (pos), 0.817693 (neg) | |
| data reader: epoch = 0, batch = 719 / 4040 | |
| iter = 719, cls_loss (cur) = 0.408612, cls_loss (avg) = 0.429896, lr = 0.010000 | |
| iter = 719, accuracy (cur) = 0.820000 (all), 0.684211 (pos), 0.903226 (neg) | |
| iter = 719, accuracy (avg) = 0.801730 (all), 0.785779 (pos), 0.818549 (neg) | |
| data reader: epoch = 0, batch = 720 / 4040 | |
| iter = 720, cls_loss (cur) = 0.379010, cls_loss (avg) = 0.429388, lr = 0.010000 | |
| iter = 720, accuracy (cur) = 0.820000 (all), 0.714286 (pos), 0.896552 (neg) | |
| iter = 720, accuracy (avg) = 0.801913 (all), 0.785064 (pos), 0.819329 (neg) | |
| data reader: epoch = 0, batch = 721 / 4040 | |
| iter = 721, cls_loss (cur) = 0.466847, cls_loss (avg) = 0.429762, lr = 0.010000 | |
| iter = 721, accuracy (cur) = 0.800000 (all), 0.791667 (pos), 0.807692 (neg) | |
| iter = 721, accuracy (avg) = 0.801894 (all), 0.785130 (pos), 0.819212 (neg) | |
| data reader: epoch = 0, batch = 722 / 4040 | |
| iter = 722, cls_loss (cur) = 0.420345, cls_loss (avg) = 0.429668, lr = 0.010000 | |
| iter = 722, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.941176 (neg) | |
| iter = 722, accuracy (avg) = 0.801875 (all), 0.784552 (pos), 0.820432 (neg) | |
| data reader: epoch = 0, batch = 723 / 4040 | |
| iter = 723, cls_loss (cur) = 0.341208, cls_loss (avg) = 0.428783, lr = 0.010000 | |
| iter = 723, accuracy (cur) = 0.820000 (all), 0.733333 (pos), 0.950000 (neg) | |
| iter = 723, accuracy (avg) = 0.802056 (all), 0.784039 (pos), 0.821728 (neg) | |
| data reader: epoch = 0, batch = 724 / 4040 | |
| iter = 724, cls_loss (cur) = 0.491888, cls_loss (avg) = 0.429414, lr = 0.010000 | |
| iter = 724, accuracy (cur) = 0.640000 (all), 0.600000 (pos), 0.700000 (neg) | |
| iter = 724, accuracy (avg) = 0.800436 (all), 0.782199 (pos), 0.820510 (neg) | |
| data reader: epoch = 0, batch = 725 / 4040 | |
| iter = 725, cls_loss (cur) = 0.396572, cls_loss (avg) = 0.429086, lr = 0.010000 | |
| iter = 725, accuracy (cur) = 0.840000 (all), 0.923077 (pos), 0.750000 (neg) | |
| iter = 725, accuracy (avg) = 0.800831 (all), 0.783608 (pos), 0.819805 (neg) | |
| data reader: epoch = 0, batch = 726 / 4040 | |
| iter = 726, cls_loss (cur) = 0.436600, cls_loss (avg) = 0.429161, lr = 0.010000 | |
| iter = 726, accuracy (cur) = 0.820000 (all), 0.913043 (pos), 0.740741 (neg) | |
| iter = 726, accuracy (avg) = 0.801023 (all), 0.784902 (pos), 0.819015 (neg) | |
| data reader: epoch = 0, batch = 727 / 4040 | |
| iter = 727, cls_loss (cur) = 0.515926, cls_loss (avg) = 0.430029, lr = 0.010000 | |
| iter = 727, accuracy (cur) = 0.680000 (all), 0.772727 (pos), 0.607143 (neg) | |
| iter = 727, accuracy (avg) = 0.799813 (all), 0.784780 (pos), 0.816896 (neg) | |
| data reader: epoch = 0, batch = 728 / 4040 | |
| iter = 728, cls_loss (cur) = 0.404102, cls_loss (avg) = 0.429770, lr = 0.010000 | |
| iter = 728, accuracy (cur) = 0.760000 (all), 0.848485 (pos), 0.588235 (neg) | |
| iter = 728, accuracy (avg) = 0.799415 (all), 0.785417 (pos), 0.814609 (neg) | |
| data reader: epoch = 0, batch = 729 / 4040 | |
| iter = 729, cls_loss (cur) = 0.321400, cls_loss (avg) = 0.428686, lr = 0.010000 | |
| iter = 729, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 729, accuracy (avg) = 0.800021 (all), 0.786452 (pos), 0.814724 (neg) | |
| data reader: epoch = 0, batch = 730 / 4040 | |
| iter = 730, cls_loss (cur) = 0.385034, cls_loss (avg) = 0.428249, lr = 0.010000 | |
| iter = 730, accuracy (cur) = 0.840000 (all), 1.000000 (pos), 0.692308 (neg) | |
| iter = 730, accuracy (avg) = 0.800420 (all), 0.788588 (pos), 0.813500 (neg) | |
| data reader: epoch = 0, batch = 731 / 4040 | |
| iter = 731, cls_loss (cur) = 0.441685, cls_loss (avg) = 0.428384, lr = 0.010000 | |
| iter = 731, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.827586 (neg) | |
| iter = 731, accuracy (avg) = 0.800016 (all), 0.787368 (pos), 0.813641 (neg) | |
| data reader: epoch = 0, batch = 732 / 4040 | |
| iter = 732, cls_loss (cur) = 0.392851, cls_loss (avg) = 0.428028, lr = 0.010000 | |
| iter = 732, accuracy (cur) = 0.800000 (all), 0.781250 (pos), 0.833333 (neg) | |
| iter = 732, accuracy (avg) = 0.800016 (all), 0.787307 (pos), 0.813838 (neg) | |
| data reader: epoch = 0, batch = 733 / 4040 | |
| iter = 733, cls_loss (cur) = 0.446744, cls_loss (avg) = 0.428215, lr = 0.010000 | |
| iter = 733, accuracy (cur) = 0.780000 (all), 0.700000 (pos), 0.833333 (neg) | |
| iter = 733, accuracy (avg) = 0.799816 (all), 0.786434 (pos), 0.814033 (neg) | |
| data reader: epoch = 0, batch = 734 / 4040 | |
| iter = 734, cls_loss (cur) = 0.433416, cls_loss (avg) = 0.428268, lr = 0.010000 | |
| iter = 734, accuracy (cur) = 0.780000 (all), 0.724138 (pos), 0.857143 (neg) | |
| iter = 734, accuracy (avg) = 0.799618 (all), 0.785811 (pos), 0.814464 (neg) | |
| data reader: epoch = 0, batch = 735 / 4040 | |
| iter = 735, cls_loss (cur) = 0.330993, cls_loss (avg) = 0.427295, lr = 0.010000 | |
| iter = 735, accuracy (cur) = 0.820000 (all), 0.923077 (pos), 0.783784 (neg) | |
| iter = 735, accuracy (avg) = 0.799822 (all), 0.787184 (pos), 0.814157 (neg) | |
| data reader: epoch = 0, batch = 736 / 4040 | |
| iter = 736, cls_loss (cur) = 0.497305, cls_loss (avg) = 0.427995, lr = 0.010000 | |
| iter = 736, accuracy (cur) = 0.760000 (all), 0.700000 (pos), 0.850000 (neg) | |
| iter = 736, accuracy (avg) = 0.799423 (all), 0.786312 (pos), 0.814515 (neg) | |
| data reader: epoch = 0, batch = 737 / 4040 | |
| iter = 737, cls_loss (cur) = 0.456468, cls_loss (avg) = 0.428280, lr = 0.010000 | |
| iter = 737, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.846154 (neg) | |
| iter = 737, accuracy (avg) = 0.799429 (all), 0.785949 (pos), 0.814832 (neg) | |
| data reader: epoch = 0, batch = 738 / 4040 | |
| iter = 738, cls_loss (cur) = 0.525049, cls_loss (avg) = 0.429247, lr = 0.010000 | |
| iter = 738, accuracy (cur) = 0.680000 (all), 0.500000 (pos), 0.781250 (neg) | |
| iter = 738, accuracy (avg) = 0.798235 (all), 0.783089 (pos), 0.814496 (neg) | |
| data reader: epoch = 0, batch = 739 / 4040 | |
| iter = 739, cls_loss (cur) = 0.442546, cls_loss (avg) = 0.429380, lr = 0.010000 | |
| iter = 739, accuracy (cur) = 0.840000 (all), 0.826087 (pos), 0.851852 (neg) | |
| iter = 739, accuracy (avg) = 0.798652 (all), 0.783519 (pos), 0.814870 (neg) | |
| data reader: epoch = 0, batch = 740 / 4040 | |
| iter = 740, cls_loss (cur) = 0.374928, cls_loss (avg) = 0.428836, lr = 0.010000 | |
| iter = 740, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 740, accuracy (avg) = 0.799066 (all), 0.783615 (pos), 0.815768 (neg) | |
| data reader: epoch = 0, batch = 741 / 4040 | |
| iter = 741, cls_loss (cur) = 0.396044, cls_loss (avg) = 0.428508, lr = 0.010000 | |
| iter = 741, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 741, accuracy (avg) = 0.800075 (all), 0.784946 (pos), 0.816457 (neg) | |
| data reader: epoch = 0, batch = 742 / 4040 | |
| iter = 742, cls_loss (cur) = 0.530152, cls_loss (avg) = 0.429524, lr = 0.010000 | |
| iter = 742, accuracy (cur) = 0.760000 (all), 0.777778 (pos), 0.739130 (neg) | |
| iter = 742, accuracy (avg) = 0.799674 (all), 0.784874 (pos), 0.815684 (neg) | |
| data reader: epoch = 0, batch = 743 / 4040 | |
| iter = 743, cls_loss (cur) = 0.421864, cls_loss (avg) = 0.429448, lr = 0.010000 | |
| iter = 743, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 743, accuracy (avg) = 0.799878 (all), 0.784625 (pos), 0.816327 (neg) | |
| data reader: epoch = 0, batch = 744 / 4040 | |
| iter = 744, cls_loss (cur) = 0.429511, cls_loss (avg) = 0.429448, lr = 0.010000 | |
| iter = 744, accuracy (cur) = 0.800000 (all), 0.722222 (pos), 0.843750 (neg) | |
| iter = 744, accuracy (avg) = 0.799879 (all), 0.784001 (pos), 0.816601 (neg) | |
| data reader: epoch = 0, batch = 745 / 4040 | |
| iter = 745, cls_loss (cur) = 0.313861, cls_loss (avg) = 0.428292, lr = 0.010000 | |
| iter = 745, accuracy (cur) = 0.920000 (all), 0.966667 (pos), 0.850000 (neg) | |
| iter = 745, accuracy (avg) = 0.801080 (all), 0.785828 (pos), 0.816935 (neg) | |
| data reader: epoch = 0, batch = 746 / 4040 | |
| iter = 746, cls_loss (cur) = 0.402237, cls_loss (avg) = 0.428032, lr = 0.010000 | |
| iter = 746, accuracy (cur) = 0.820000 (all), 0.840000 (pos), 0.800000 (neg) | |
| iter = 746, accuracy (avg) = 0.801269 (all), 0.786370 (pos), 0.816766 (neg) | |
| data reader: epoch = 0, batch = 747 / 4040 | |
| iter = 747, cls_loss (cur) = 0.467852, cls_loss (avg) = 0.428430, lr = 0.010000 | |
| iter = 747, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.730769 (neg) | |
| iter = 747, accuracy (avg) = 0.800657 (all), 0.786006 (pos), 0.815906 (neg) | |
| data reader: epoch = 0, batch = 748 / 4040 | |
| iter = 748, cls_loss (cur) = 0.346690, cls_loss (avg) = 0.427613, lr = 0.010000 | |
| iter = 748, accuracy (cur) = 0.840000 (all), 0.782609 (pos), 0.888889 (neg) | |
| iter = 748, accuracy (avg) = 0.801050 (all), 0.785972 (pos), 0.816636 (neg) | |
| data reader: epoch = 0, batch = 749 / 4040 | |
| iter = 749, cls_loss (cur) = 0.349776, cls_loss (avg) = 0.426834, lr = 0.010000 | |
| iter = 749, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 749, accuracy (avg) = 0.801440 (all), 0.786208 (pos), 0.817090 (neg) | |
| data reader: epoch = 0, batch = 750 / 4040 | |
| iter = 750, cls_loss (cur) = 0.353742, cls_loss (avg) = 0.426103, lr = 0.010000 | |
| iter = 750, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 750, accuracy (avg) = 0.802225 (all), 0.787545 (pos), 0.817319 (neg) | |
| data reader: epoch = 0, batch = 751 / 4040 | |
| iter = 751, cls_loss (cur) = 0.456608, cls_loss (avg) = 0.426408, lr = 0.010000 | |
| iter = 751, accuracy (cur) = 0.760000 (all), 0.642857 (pos), 0.909091 (neg) | |
| iter = 751, accuracy (avg) = 0.801803 (all), 0.786099 (pos), 0.818237 (neg) | |
| data reader: epoch = 0, batch = 752 / 4040 | |
| iter = 752, cls_loss (cur) = 0.335923, cls_loss (avg) = 0.425504, lr = 0.010000 | |
| iter = 752, accuracy (cur) = 0.900000 (all), 0.956522 (pos), 0.851852 (neg) | |
| iter = 752, accuracy (avg) = 0.802785 (all), 0.787803 (pos), 0.818573 (neg) | |
| data reader: epoch = 0, batch = 753 / 4040 | |
| iter = 753, cls_loss (cur) = 0.380917, cls_loss (avg) = 0.425058, lr = 0.010000 | |
| iter = 753, accuracy (cur) = 0.860000 (all), 0.950000 (pos), 0.800000 (neg) | |
| iter = 753, accuracy (avg) = 0.803357 (all), 0.789425 (pos), 0.818387 (neg) | |
| data reader: epoch = 0, batch = 754 / 4040 | |
| iter = 754, cls_loss (cur) = 0.408275, cls_loss (avg) = 0.424890, lr = 0.010000 | |
| iter = 754, accuracy (cur) = 0.840000 (all), 0.888889 (pos), 0.782609 (neg) | |
| iter = 754, accuracy (avg) = 0.803724 (all), 0.790419 (pos), 0.818029 (neg) | |
| data reader: epoch = 0, batch = 755 / 4040 | |
| iter = 755, cls_loss (cur) = 0.358937, cls_loss (avg) = 0.424230, lr = 0.010000 | |
| iter = 755, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 755, accuracy (avg) = 0.804286 (all), 0.791315 (pos), 0.818249 (neg) | |
| data reader: epoch = 0, batch = 756 / 4040 | |
| iter = 756, cls_loss (cur) = 0.432827, cls_loss (avg) = 0.424316, lr = 0.010000 | |
| iter = 756, accuracy (cur) = 0.780000 (all), 0.703704 (pos), 0.869565 (neg) | |
| iter = 756, accuracy (avg) = 0.804043 (all), 0.790439 (pos), 0.818762 (neg) | |
| data reader: epoch = 0, batch = 757 / 4040 | |
| iter = 757, cls_loss (cur) = 0.516105, cls_loss (avg) = 0.425234, lr = 0.010000 | |
| iter = 757, accuracy (cur) = 0.800000 (all), 0.766667 (pos), 0.850000 (neg) | |
| iter = 757, accuracy (avg) = 0.804003 (all), 0.790201 (pos), 0.819075 (neg) | |
| data reader: epoch = 0, batch = 758 / 4040 | |
| iter = 758, cls_loss (cur) = 0.315884, cls_loss (avg) = 0.424141, lr = 0.010000 | |
| iter = 758, accuracy (cur) = 0.840000 (all), 0.769231 (pos), 0.916667 (neg) | |
| iter = 758, accuracy (avg) = 0.804363 (all), 0.789992 (pos), 0.820051 (neg) | |
| data reader: epoch = 0, batch = 759 / 4040 | |
| iter = 759, cls_loss (cur) = 0.330983, cls_loss (avg) = 0.423209, lr = 0.010000 | |
| iter = 759, accuracy (cur) = 0.900000 (all), 0.842105 (pos), 0.935484 (neg) | |
| iter = 759, accuracy (avg) = 0.805319 (all), 0.790513 (pos), 0.821205 (neg) | |
| data reader: epoch = 0, batch = 760 / 4040 | |
| iter = 760, cls_loss (cur) = 0.421840, cls_loss (avg) = 0.423195, lr = 0.010000 | |
| iter = 760, accuracy (cur) = 0.760000 (all), 0.791667 (pos), 0.730769 (neg) | |
| iter = 760, accuracy (avg) = 0.804866 (all), 0.790524 (pos), 0.820300 (neg) | |
| data reader: epoch = 0, batch = 761 / 4040 | |
| iter = 761, cls_loss (cur) = 0.412919, cls_loss (avg) = 0.423093, lr = 0.010000 | |
| iter = 761, accuracy (cur) = 0.820000 (all), 0.777778 (pos), 0.869565 (neg) | |
| iter = 761, accuracy (avg) = 0.805017 (all), 0.790397 (pos), 0.820793 (neg) | |
| data reader: epoch = 0, batch = 762 / 4040 | |
| iter = 762, cls_loss (cur) = 0.359300, cls_loss (avg) = 0.422455, lr = 0.010000 | |
| iter = 762, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 762, accuracy (avg) = 0.805767 (all), 0.791293 (pos), 0.821385 (neg) | |
| data reader: epoch = 0, batch = 763 / 4040 | |
| iter = 763, cls_loss (cur) = 0.378792, cls_loss (avg) = 0.422018, lr = 0.010000 | |
| iter = 763, accuracy (cur) = 0.780000 (all), 0.625000 (pos), 0.923077 (neg) | |
| iter = 763, accuracy (avg) = 0.805510 (all), 0.789630 (pos), 0.822402 (neg) | |
| data reader: epoch = 0, batch = 764 / 4040 | |
| iter = 764, cls_loss (cur) = 0.425415, cls_loss (avg) = 0.422052, lr = 0.010000 | |
| iter = 764, accuracy (cur) = 0.740000 (all), 0.791667 (pos), 0.692308 (neg) | |
| iter = 764, accuracy (avg) = 0.804855 (all), 0.789650 (pos), 0.821101 (neg) | |
| data reader: epoch = 0, batch = 765 / 4040 | |
| iter = 765, cls_loss (cur) = 0.389490, cls_loss (avg) = 0.421727, lr = 0.010000 | |
| iter = 765, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 765, accuracy (avg) = 0.805206 (all), 0.789754 (pos), 0.821557 (neg) | |
| data reader: epoch = 0, batch = 766 / 4040 | |
| iter = 766, cls_loss (cur) = 0.346675, cls_loss (avg) = 0.420976, lr = 0.010000 | |
| iter = 766, accuracy (cur) = 0.880000 (all), 0.862069 (pos), 0.904762 (neg) | |
| iter = 766, accuracy (avg) = 0.805954 (all), 0.790477 (pos), 0.822389 (neg) | |
| data reader: epoch = 0, batch = 767 / 4040 | |
| iter = 767, cls_loss (cur) = 0.419179, cls_loss (avg) = 0.420958, lr = 0.010000 | |
| iter = 767, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.909091 (neg) | |
| iter = 767, accuracy (avg) = 0.806094 (all), 0.790072 (pos), 0.823256 (neg) | |
| data reader: epoch = 0, batch = 768 / 4040 | |
| iter = 768, cls_loss (cur) = 0.399165, cls_loss (avg) = 0.420740, lr = 0.010000 | |
| iter = 768, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 768, accuracy (avg) = 0.806433 (all), 0.790248 (pos), 0.823773 (neg) | |
| data reader: epoch = 0, batch = 769 / 4040 | |
| iter = 769, cls_loss (cur) = 0.438296, cls_loss (avg) = 0.420916, lr = 0.010000 | |
| iter = 769, accuracy (cur) = 0.740000 (all), 0.653846 (pos), 0.833333 (neg) | |
| iter = 769, accuracy (avg) = 0.805769 (all), 0.788884 (pos), 0.823869 (neg) | |
| data reader: epoch = 0, batch = 770 / 4040 | |
| iter = 770, cls_loss (cur) = 0.372486, cls_loss (avg) = 0.420431, lr = 0.010000 | |
| iter = 770, accuracy (cur) = 0.820000 (all), 0.740741 (pos), 0.913043 (neg) | |
| iter = 770, accuracy (avg) = 0.805911 (all), 0.788403 (pos), 0.824761 (neg) | |
| data reader: epoch = 0, batch = 771 / 4040 | |
| iter = 771, cls_loss (cur) = 0.366226, cls_loss (avg) = 0.419889, lr = 0.010000 | |
| iter = 771, accuracy (cur) = 0.900000 (all), 0.869565 (pos), 0.925926 (neg) | |
| iter = 771, accuracy (avg) = 0.806852 (all), 0.789215 (pos), 0.825772 (neg) | |
| data reader: epoch = 0, batch = 772 / 4040 | |
| iter = 772, cls_loss (cur) = 0.445171, cls_loss (avg) = 0.420142, lr = 0.010000 | |
| iter = 772, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 772, accuracy (avg) = 0.806984 (all), 0.789149 (pos), 0.826033 (neg) | |
| data reader: epoch = 0, batch = 773 / 4040 | |
| iter = 773, cls_loss (cur) = 0.299689, cls_loss (avg) = 0.418938, lr = 0.010000 | |
| iter = 773, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 773, accuracy (avg) = 0.807714 (all), 0.789719 (pos), 0.826939 (neg) | |
| data reader: epoch = 0, batch = 774 / 4040 | |
| iter = 774, cls_loss (cur) = 0.425827, cls_loss (avg) = 0.419006, lr = 0.010000 | |
| iter = 774, accuracy (cur) = 0.760000 (all), 0.793103 (pos), 0.714286 (neg) | |
| iter = 774, accuracy (avg) = 0.807237 (all), 0.789752 (pos), 0.825813 (neg) | |
| data reader: epoch = 0, batch = 775 / 4040 | |
| iter = 775, cls_loss (cur) = 0.393475, cls_loss (avg) = 0.418751, lr = 0.010000 | |
| iter = 775, accuracy (cur) = 0.800000 (all), 0.956522 (pos), 0.666667 (neg) | |
| iter = 775, accuracy (avg) = 0.807164 (all), 0.791420 (pos), 0.824221 (neg) | |
| data reader: epoch = 0, batch = 776 / 4040 | |
| iter = 776, cls_loss (cur) = 0.392744, cls_loss (avg) = 0.418491, lr = 0.010000 | |
| iter = 776, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 776, accuracy (avg) = 0.807093 (all), 0.791688 (pos), 0.823836 (neg) | |
| data reader: epoch = 0, batch = 777 / 4040 | |
| iter = 777, cls_loss (cur) = 0.401865, cls_loss (avg) = 0.418325, lr = 0.010000 | |
| iter = 777, accuracy (cur) = 0.760000 (all), 0.740741 (pos), 0.782609 (neg) | |
| iter = 777, accuracy (avg) = 0.806622 (all), 0.791178 (pos), 0.823424 (neg) | |
| data reader: epoch = 0, batch = 778 / 4040 | |
| iter = 778, cls_loss (cur) = 0.343903, cls_loss (avg) = 0.417581, lr = 0.010000 | |
| iter = 778, accuracy (cur) = 0.840000 (all), 0.772727 (pos), 0.892857 (neg) | |
| iter = 778, accuracy (avg) = 0.806956 (all), 0.790994 (pos), 0.824118 (neg) | |
| data reader: epoch = 0, batch = 779 / 4040 | |
| iter = 779, cls_loss (cur) = 0.342846, cls_loss (avg) = 0.416833, lr = 0.010000 | |
| iter = 779, accuracy (cur) = 0.900000 (all), 0.826087 (pos), 0.962963 (neg) | |
| iter = 779, accuracy (avg) = 0.807886 (all), 0.791345 (pos), 0.825507 (neg) | |
| data reader: epoch = 0, batch = 780 / 4040 | |
| iter = 780, cls_loss (cur) = 0.308481, cls_loss (avg) = 0.415750, lr = 0.010000 | |
| iter = 780, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 780, accuracy (avg) = 0.808607 (all), 0.791692 (pos), 0.826511 (neg) | |
| data reader: epoch = 0, batch = 781 / 4040 | |
| iter = 781, cls_loss (cur) = 0.335308, cls_loss (avg) = 0.414945, lr = 0.010000 | |
| iter = 781, accuracy (cur) = 0.860000 (all), 0.700000 (pos), 0.966667 (neg) | |
| iter = 781, accuracy (avg) = 0.809121 (all), 0.790775 (pos), 0.827913 (neg) | |
| data reader: epoch = 0, batch = 782 / 4040 | |
| iter = 782, cls_loss (cur) = 0.467945, cls_loss (avg) = 0.415475, lr = 0.010000 | |
| iter = 782, accuracy (cur) = 0.700000 (all), 0.650000 (pos), 0.733333 (neg) | |
| iter = 782, accuracy (avg) = 0.808030 (all), 0.789367 (pos), 0.826967 (neg) | |
| data reader: epoch = 0, batch = 783 / 4040 | |
| iter = 783, cls_loss (cur) = 0.515592, cls_loss (avg) = 0.416477, lr = 0.010000 | |
| iter = 783, accuracy (cur) = 0.700000 (all), 0.800000 (pos), 0.633333 (neg) | |
| iter = 783, accuracy (avg) = 0.806950 (all), 0.789474 (pos), 0.825031 (neg) | |
| data reader: epoch = 0, batch = 784 / 4040 | |
| iter = 784, cls_loss (cur) = 0.339788, cls_loss (avg) = 0.415710, lr = 0.010000 | |
| iter = 784, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 784, accuracy (avg) = 0.807280 (all), 0.789496 (pos), 0.825626 (neg) | |
| data reader: epoch = 0, batch = 785 / 4040 | |
| iter = 785, cls_loss (cur) = 0.431459, cls_loss (avg) = 0.415867, lr = 0.010000 | |
| iter = 785, accuracy (cur) = 0.720000 (all), 0.666667 (pos), 0.782609 (neg) | |
| iter = 785, accuracy (avg) = 0.806407 (all), 0.788267 (pos), 0.825196 (neg) | |
| data reader: epoch = 0, batch = 786 / 4040 | |
| iter = 786, cls_loss (cur) = 0.338387, cls_loss (avg) = 0.415092, lr = 0.010000 | |
| iter = 786, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 786, accuracy (avg) = 0.807143 (all), 0.789585 (pos), 0.825344 (neg) | |
| data reader: epoch = 0, batch = 787 / 4040 | |
| iter = 787, cls_loss (cur) = 0.334325, cls_loss (avg) = 0.414285, lr = 0.010000 | |
| iter = 787, accuracy (cur) = 0.880000 (all), 0.850000 (pos), 0.900000 (neg) | |
| iter = 787, accuracy (avg) = 0.807872 (all), 0.790189 (pos), 0.826091 (neg) | |
| data reader: epoch = 0, batch = 788 / 4040 | |
| iter = 788, cls_loss (cur) = 0.394590, cls_loss (avg) = 0.414088, lr = 0.010000 | |
| iter = 788, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.818182 (neg) | |
| iter = 788, accuracy (avg) = 0.807593 (all), 0.789787 (pos), 0.826012 (neg) | |
| data reader: epoch = 0, batch = 789 / 4040 | |
| iter = 789, cls_loss (cur) = 0.418600, cls_loss (avg) = 0.414133, lr = 0.010000 | |
| iter = 789, accuracy (cur) = 0.800000 (all), 0.761905 (pos), 0.827586 (neg) | |
| iter = 789, accuracy (avg) = 0.807517 (all), 0.789508 (pos), 0.826027 (neg) | |
| data reader: epoch = 0, batch = 790 / 4040 | |
| iter = 790, cls_loss (cur) = 0.461240, cls_loss (avg) = 0.414604, lr = 0.010000 | |
| iter = 790, accuracy (cur) = 0.760000 (all), 0.827586 (pos), 0.666667 (neg) | |
| iter = 790, accuracy (avg) = 0.807042 (all), 0.789889 (pos), 0.824434 (neg) | |
| data reader: epoch = 0, batch = 791 / 4040 | |
| iter = 791, cls_loss (cur) = 0.396477, cls_loss (avg) = 0.414423, lr = 0.010000 | |
| iter = 791, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 791, accuracy (avg) = 0.807572 (all), 0.790879 (pos), 0.824450 (neg) | |
| data reader: epoch = 0, batch = 792 / 4040 | |
| iter = 792, cls_loss (cur) = 0.361080, cls_loss (avg) = 0.413889, lr = 0.010000 | |
| iter = 792, accuracy (cur) = 0.840000 (all), 0.866667 (pos), 0.800000 (neg) | |
| iter = 792, accuracy (avg) = 0.807896 (all), 0.791637 (pos), 0.824206 (neg) | |
| data reader: epoch = 0, batch = 793 / 4040 | |
| iter = 793, cls_loss (cur) = 0.341854, cls_loss (avg) = 0.413169, lr = 0.010000 | |
| iter = 793, accuracy (cur) = 0.880000 (all), 0.851852 (pos), 0.913043 (neg) | |
| iter = 793, accuracy (avg) = 0.808617 (all), 0.792239 (pos), 0.825094 (neg) | |
| data reader: epoch = 0, batch = 794 / 4040 | |
| iter = 794, cls_loss (cur) = 0.459256, cls_loss (avg) = 0.413630, lr = 0.010000 | |
| iter = 794, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 794, accuracy (avg) = 0.808131 (all), 0.791354 (pos), 0.825104 (neg) | |
| data reader: epoch = 0, batch = 795 / 4040 | |
| iter = 795, cls_loss (cur) = 0.277499, cls_loss (avg) = 0.412268, lr = 0.010000 | |
| iter = 795, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 795, accuracy (avg) = 0.808849 (all), 0.792076 (pos), 0.825782 (neg) | |
| data reader: epoch = 0, batch = 796 / 4040 | |
| iter = 796, cls_loss (cur) = 0.410544, cls_loss (avg) = 0.412251, lr = 0.010000 | |
| iter = 796, accuracy (cur) = 0.740000 (all), 0.761905 (pos), 0.724138 (neg) | |
| iter = 796, accuracy (avg) = 0.808161 (all), 0.791775 (pos), 0.824765 (neg) | |
| data reader: epoch = 0, batch = 797 / 4040 | |
| iter = 797, cls_loss (cur) = 0.483495, cls_loss (avg) = 0.412964, lr = 0.010000 | |
| iter = 797, accuracy (cur) = 0.740000 (all), 0.850000 (pos), 0.666667 (neg) | |
| iter = 797, accuracy (avg) = 0.807479 (all), 0.792357 (pos), 0.823184 (neg) | |
| data reader: epoch = 0, batch = 798 / 4040 | |
| iter = 798, cls_loss (cur) = 0.297395, cls_loss (avg) = 0.411808, lr = 0.010000 | |
| iter = 798, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 798, accuracy (avg) = 0.808405 (all), 0.793322 (pos), 0.824083 (neg) | |
| data reader: epoch = 0, batch = 799 / 4040 | |
| iter = 799, cls_loss (cur) = 0.553653, cls_loss (avg) = 0.413226, lr = 0.010000 | |
| iter = 799, accuracy (cur) = 0.680000 (all), 0.760000 (pos), 0.600000 (neg) | |
| iter = 799, accuracy (avg) = 0.807120 (all), 0.792989 (pos), 0.821842 (neg) | |
| data reader: epoch = 0, batch = 800 / 4040 | |
| iter = 800, cls_loss (cur) = 0.297001, cls_loss (avg) = 0.412064, lr = 0.010000 | |
| iter = 800, accuracy (cur) = 0.840000 (all), 0.900000 (pos), 0.800000 (neg) | |
| iter = 800, accuracy (avg) = 0.807449 (all), 0.794059 (pos), 0.821624 (neg) | |
| data reader: epoch = 0, batch = 801 / 4040 | |
| iter = 801, cls_loss (cur) = 0.328091, cls_loss (avg) = 0.411224, lr = 0.010000 | |
| iter = 801, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 801, accuracy (avg) = 0.808175 (all), 0.794519 (pos), 0.822607 (neg) | |
| data reader: epoch = 0, batch = 802 / 4040 | |
| iter = 802, cls_loss (cur) = 0.619637, cls_loss (avg) = 0.413308, lr = 0.010000 | |
| iter = 802, accuracy (cur) = 0.680000 (all), 0.548387 (pos), 0.894737 (neg) | |
| iter = 802, accuracy (avg) = 0.806893 (all), 0.792057 (pos), 0.823329 (neg) | |
| data reader: epoch = 0, batch = 803 / 4040 | |
| iter = 803, cls_loss (cur) = 0.418892, cls_loss (avg) = 0.413364, lr = 0.010000 | |
| iter = 803, accuracy (cur) = 0.820000 (all), 0.863636 (pos), 0.785714 (neg) | |
| iter = 803, accuracy (avg) = 0.807024 (all), 0.792773 (pos), 0.822953 (neg) | |
| data reader: epoch = 0, batch = 804 / 4040 | |
| iter = 804, cls_loss (cur) = 0.358238, cls_loss (avg) = 0.412813, lr = 0.010000 | |
| iter = 804, accuracy (cur) = 0.860000 (all), 0.863636 (pos), 0.857143 (neg) | |
| iter = 804, accuracy (avg) = 0.807554 (all), 0.793482 (pos), 0.823294 (neg) | |
| data reader: epoch = 0, batch = 805 / 4040 | |
| iter = 805, cls_loss (cur) = 0.502192, cls_loss (avg) = 0.413707, lr = 0.010000 | |
| iter = 805, accuracy (cur) = 0.720000 (all), 0.692308 (pos), 0.750000 (neg) | |
| iter = 805, accuracy (avg) = 0.806678 (all), 0.792470 (pos), 0.822561 (neg) | |
| data reader: epoch = 0, batch = 806 / 4040 | |
| iter = 806, cls_loss (cur) = 0.411313, cls_loss (avg) = 0.413683, lr = 0.010000 | |
| iter = 806, accuracy (cur) = 0.820000 (all), 0.740741 (pos), 0.913043 (neg) | |
| iter = 806, accuracy (avg) = 0.806812 (all), 0.791953 (pos), 0.823466 (neg) | |
| data reader: epoch = 0, batch = 807 / 4040 | |
| iter = 807, cls_loss (cur) = 0.442962, cls_loss (avg) = 0.413976, lr = 0.010000 | |
| iter = 807, accuracy (cur) = 0.740000 (all), 0.681818 (pos), 0.785714 (neg) | |
| iter = 807, accuracy (avg) = 0.806143 (all), 0.790851 (pos), 0.823089 (neg) | |
| data reader: epoch = 0, batch = 808 / 4040 | |
| iter = 808, cls_loss (cur) = 0.448354, cls_loss (avg) = 0.414319, lr = 0.010000 | |
| iter = 808, accuracy (cur) = 0.780000 (all), 0.850000 (pos), 0.733333 (neg) | |
| iter = 808, accuracy (avg) = 0.805882 (all), 0.791443 (pos), 0.822191 (neg) | |
| data reader: epoch = 0, batch = 809 / 4040 | |
| iter = 809, cls_loss (cur) = 0.407061, cls_loss (avg) = 0.414247, lr = 0.010000 | |
| iter = 809, accuracy (cur) = 0.780000 (all), 0.809524 (pos), 0.758621 (neg) | |
| iter = 809, accuracy (avg) = 0.805623 (all), 0.791624 (pos), 0.821556 (neg) | |
| data reader: epoch = 0, batch = 810 / 4040 | |
| iter = 810, cls_loss (cur) = 0.274720, cls_loss (avg) = 0.412852, lr = 0.010000 | |
| iter = 810, accuracy (cur) = 0.900000 (all), 0.962963 (pos), 0.826087 (neg) | |
| iter = 810, accuracy (avg) = 0.806567 (all), 0.793337 (pos), 0.821601 (neg) | |
| data reader: epoch = 0, batch = 811 / 4040 | |
| iter = 811, cls_loss (cur) = 0.432112, cls_loss (avg) = 0.413044, lr = 0.010000 | |
| iter = 811, accuracy (cur) = 0.800000 (all), 0.681818 (pos), 0.892857 (neg) | |
| iter = 811, accuracy (avg) = 0.806501 (all), 0.792222 (pos), 0.822313 (neg) | |
| data reader: epoch = 0, batch = 812 / 4040 | |
| iter = 812, cls_loss (cur) = 0.518432, cls_loss (avg) = 0.414098, lr = 0.010000 | |
| iter = 812, accuracy (cur) = 0.760000 (all), 0.619048 (pos), 0.862069 (neg) | |
| iter = 812, accuracy (avg) = 0.806036 (all), 0.790490 (pos), 0.822711 (neg) | |
| data reader: epoch = 0, batch = 813 / 4040 | |
| iter = 813, cls_loss (cur) = 0.358566, cls_loss (avg) = 0.413543, lr = 0.010000 | |
| iter = 813, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 813, accuracy (avg) = 0.806376 (all), 0.790585 (pos), 0.823151 (neg) | |
| data reader: epoch = 0, batch = 814 / 4040 | |
| iter = 814, cls_loss (cur) = 0.438592, cls_loss (avg) = 0.413793, lr = 0.010000 | |
| iter = 814, accuracy (cur) = 0.820000 (all), 0.724138 (pos), 0.952381 (neg) | |
| iter = 814, accuracy (avg) = 0.806512 (all), 0.789921 (pos), 0.824443 (neg) | |
| data reader: epoch = 0, batch = 815 / 4040 | |
| iter = 815, cls_loss (cur) = 0.462927, cls_loss (avg) = 0.414285, lr = 0.010000 | |
| iter = 815, accuracy (cur) = 0.740000 (all), 0.714286 (pos), 0.758621 (neg) | |
| iter = 815, accuracy (avg) = 0.805847 (all), 0.789164 (pos), 0.823785 (neg) | |
| data reader: epoch = 0, batch = 816 / 4040 | |
| iter = 816, cls_loss (cur) = 0.343443, cls_loss (avg) = 0.413576, lr = 0.010000 | |
| iter = 816, accuracy (cur) = 0.860000 (all), 0.761905 (pos), 0.931034 (neg) | |
| iter = 816, accuracy (avg) = 0.806389 (all), 0.788892 (pos), 0.824857 (neg) | |
| data reader: epoch = 0, batch = 817 / 4040 | |
| iter = 817, cls_loss (cur) = 0.433248, cls_loss (avg) = 0.413773, lr = 0.010000 | |
| iter = 817, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 817, accuracy (avg) = 0.806725 (all), 0.789403 (pos), 0.825009 (neg) | |
| data reader: epoch = 0, batch = 818 / 4040 | |
| iter = 818, cls_loss (cur) = 0.409636, cls_loss (avg) = 0.413732, lr = 0.010000 | |
| iter = 818, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 818, accuracy (avg) = 0.807057 (all), 0.789842 (pos), 0.825220 (neg) | |
| data reader: epoch = 0, batch = 819 / 4040 | |
| iter = 819, cls_loss (cur) = 0.440073, cls_loss (avg) = 0.413995, lr = 0.010000 | |
| iter = 819, accuracy (cur) = 0.780000 (all), 0.700000 (pos), 0.833333 (neg) | |
| iter = 819, accuracy (avg) = 0.806787 (all), 0.788944 (pos), 0.825301 (neg) | |
| data reader: epoch = 0, batch = 820 / 4040 | |
| iter = 820, cls_loss (cur) = 0.417799, cls_loss (avg) = 0.414033, lr = 0.010000 | |
| iter = 820, accuracy (cur) = 0.860000 (all), 0.863636 (pos), 0.857143 (neg) | |
| iter = 820, accuracy (avg) = 0.807319 (all), 0.789691 (pos), 0.825620 (neg) | |
| data reader: epoch = 0, batch = 821 / 4040 | |
| iter = 821, cls_loss (cur) = 0.413553, cls_loss (avg) = 0.414028, lr = 0.010000 | |
| iter = 821, accuracy (cur) = 0.820000 (all), 0.695652 (pos), 0.925926 (neg) | |
| iter = 821, accuracy (avg) = 0.807446 (all), 0.788750 (pos), 0.826623 (neg) | |
| data reader: epoch = 0, batch = 822 / 4040 | |
| iter = 822, cls_loss (cur) = 0.339958, cls_loss (avg) = 0.413288, lr = 0.010000 | |
| iter = 822, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 822, accuracy (avg) = 0.807771 (all), 0.789709 (pos), 0.826273 (neg) | |
| data reader: epoch = 0, batch = 823 / 4040 | |
| iter = 823, cls_loss (cur) = 0.427368, cls_loss (avg) = 0.413428, lr = 0.010000 | |
| iter = 823, accuracy (cur) = 0.820000 (all), 0.809524 (pos), 0.827586 (neg) | |
| iter = 823, accuracy (avg) = 0.807894 (all), 0.789907 (pos), 0.826286 (neg) | |
| data reader: epoch = 0, batch = 824 / 4040 | |
| iter = 824, cls_loss (cur) = 0.475571, cls_loss (avg) = 0.414050, lr = 0.010000 | |
| iter = 824, accuracy (cur) = 0.760000 (all), 0.771429 (pos), 0.733333 (neg) | |
| iter = 824, accuracy (avg) = 0.807415 (all), 0.789722 (pos), 0.825357 (neg) | |
| data reader: epoch = 0, batch = 825 / 4040 | |
| iter = 825, cls_loss (cur) = 0.458336, cls_loss (avg) = 0.414493, lr = 0.010000 | |
| iter = 825, accuracy (cur) = 0.760000 (all), 0.652174 (pos), 0.851852 (neg) | |
| iter = 825, accuracy (avg) = 0.806941 (all), 0.788347 (pos), 0.825622 (neg) | |
| data reader: epoch = 0, batch = 826 / 4040 | |
| iter = 826, cls_loss (cur) = 0.504860, cls_loss (avg) = 0.415396, lr = 0.010000 | |
| iter = 826, accuracy (cur) = 0.700000 (all), 0.761905 (pos), 0.655172 (neg) | |
| iter = 826, accuracy (avg) = 0.805871 (all), 0.788082 (pos), 0.823917 (neg) | |
| data reader: epoch = 0, batch = 827 / 4040 | |
| iter = 827, cls_loss (cur) = 0.352904, cls_loss (avg) = 0.414771, lr = 0.010000 | |
| iter = 827, accuracy (cur) = 0.780000 (all), 0.833333 (pos), 0.730769 (neg) | |
| iter = 827, accuracy (avg) = 0.805612 (all), 0.788535 (pos), 0.822986 (neg) | |
| data reader: epoch = 0, batch = 828 / 4040 | |
| iter = 828, cls_loss (cur) = 0.382764, cls_loss (avg) = 0.414451, lr = 0.010000 | |
| iter = 828, accuracy (cur) = 0.840000 (all), 0.900000 (pos), 0.800000 (neg) | |
| iter = 828, accuracy (avg) = 0.805956 (all), 0.789650 (pos), 0.822756 (neg) | |
| data reader: epoch = 0, batch = 829 / 4040 | |
| iter = 829, cls_loss (cur) = 0.445617, cls_loss (avg) = 0.414763, lr = 0.010000 | |
| iter = 829, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.769231 (neg) | |
| iter = 829, accuracy (avg) = 0.805897 (all), 0.790086 (pos), 0.822221 (neg) | |
| data reader: epoch = 0, batch = 830 / 4040 | |
| iter = 830, cls_loss (cur) = 0.370348, cls_loss (avg) = 0.414319, lr = 0.010000 | |
| iter = 830, accuracy (cur) = 0.800000 (all), 0.760000 (pos), 0.840000 (neg) | |
| iter = 830, accuracy (avg) = 0.805838 (all), 0.789786 (pos), 0.822398 (neg) | |
| data reader: epoch = 0, batch = 831 / 4040 | |
| iter = 831, cls_loss (cur) = 0.428626, cls_loss (avg) = 0.414462, lr = 0.010000 | |
| iter = 831, accuracy (cur) = 0.820000 (all), 0.727273 (pos), 0.892857 (neg) | |
| iter = 831, accuracy (avg) = 0.805979 (all), 0.789160 (pos), 0.823103 (neg) | |
| data reader: epoch = 0, batch = 832 / 4040 | |
| iter = 832, cls_loss (cur) = 0.475230, cls_loss (avg) = 0.415070, lr = 0.010000 | |
| iter = 832, accuracy (cur) = 0.760000 (all), 0.600000 (pos), 0.866667 (neg) | |
| iter = 832, accuracy (avg) = 0.805520 (all), 0.787269 (pos), 0.823539 (neg) | |
| data reader: epoch = 0, batch = 833 / 4040 | |
| iter = 833, cls_loss (cur) = 0.419568, cls_loss (avg) = 0.415115, lr = 0.010000 | |
| iter = 833, accuracy (cur) = 0.840000 (all), 0.739130 (pos), 0.925926 (neg) | |
| iter = 833, accuracy (avg) = 0.805864 (all), 0.786787 (pos), 0.824562 (neg) | |
| data reader: epoch = 0, batch = 834 / 4040 | |
| iter = 834, cls_loss (cur) = 0.380086, cls_loss (avg) = 0.414764, lr = 0.010000 | |
| iter = 834, accuracy (cur) = 0.780000 (all), 0.631579 (pos), 0.870968 (neg) | |
| iter = 834, accuracy (avg) = 0.805606 (all), 0.785235 (pos), 0.825026 (neg) | |
| data reader: epoch = 0, batch = 835 / 4040 | |
| iter = 835, cls_loss (cur) = 0.413596, cls_loss (avg) = 0.414753, lr = 0.010000 | |
| iter = 835, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 835, accuracy (avg) = 0.805150 (all), 0.784420 (pos), 0.825037 (neg) | |
| data reader: epoch = 0, batch = 836 / 4040 | |
| iter = 836, cls_loss (cur) = 0.391296, cls_loss (avg) = 0.414518, lr = 0.010000 | |
| iter = 836, accuracy (cur) = 0.820000 (all), 0.720000 (pos), 0.920000 (neg) | |
| iter = 836, accuracy (avg) = 0.805298 (all), 0.783776 (pos), 0.825987 (neg) | |
| data reader: epoch = 0, batch = 837 / 4040 | |
| iter = 837, cls_loss (cur) = 0.424618, cls_loss (avg) = 0.414619, lr = 0.010000 | |
| iter = 837, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 837, accuracy (avg) = 0.805645 (all), 0.784015 (pos), 0.826477 (neg) | |
| data reader: epoch = 0, batch = 838 / 4040 | |
| iter = 838, cls_loss (cur) = 0.349081, cls_loss (avg) = 0.413964, lr = 0.010000 | |
| iter = 838, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 838, accuracy (avg) = 0.806189 (all), 0.784636 (pos), 0.826962 (neg) | |
| data reader: epoch = 0, batch = 839 / 4040 | |
| iter = 839, cls_loss (cur) = 0.308065, cls_loss (avg) = 0.412905, lr = 0.010000 | |
| iter = 839, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 839, accuracy (avg) = 0.806527 (all), 0.784885 (pos), 0.827313 (neg) | |
| data reader: epoch = 0, batch = 840 / 4040 | |
| iter = 840, cls_loss (cur) = 0.326007, cls_loss (avg) = 0.412036, lr = 0.010000 | |
| iter = 840, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 840, accuracy (avg) = 0.806662 (all), 0.785498 (pos), 0.826957 (neg) | |
| data reader: epoch = 0, batch = 841 / 4040 | |
| iter = 841, cls_loss (cur) = 0.444179, cls_loss (avg) = 0.412357, lr = 0.010000 | |
| iter = 841, accuracy (cur) = 0.780000 (all), 0.875000 (pos), 0.692308 (neg) | |
| iter = 841, accuracy (avg) = 0.806395 (all), 0.786393 (pos), 0.825610 (neg) | |
| data reader: epoch = 0, batch = 842 / 4040 | |
| iter = 842, cls_loss (cur) = 0.375179, cls_loss (avg) = 0.411985, lr = 0.010000 | |
| iter = 842, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 842, accuracy (avg) = 0.806531 (all), 0.786386 (pos), 0.825990 (neg) | |
| data reader: epoch = 0, batch = 843 / 4040 | |
| iter = 843, cls_loss (cur) = 0.403401, cls_loss (avg) = 0.411899, lr = 0.010000 | |
| iter = 843, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 843, accuracy (avg) = 0.807066 (all), 0.787411 (pos), 0.825991 (neg) | |
| data reader: epoch = 0, batch = 844 / 4040 | |
| iter = 844, cls_loss (cur) = 0.432143, cls_loss (avg) = 0.412102, lr = 0.010000 | |
| iter = 844, accuracy (cur) = 0.740000 (all), 0.909091 (pos), 0.607143 (neg) | |
| iter = 844, accuracy (avg) = 0.806395 (all), 0.788628 (pos), 0.823803 (neg) | |
| data reader: epoch = 0, batch = 845 / 4040 | |
| iter = 845, cls_loss (cur) = 0.406156, cls_loss (avg) = 0.412042, lr = 0.010000 | |
| iter = 845, accuracy (cur) = 0.820000 (all), 0.892857 (pos), 0.727273 (neg) | |
| iter = 845, accuracy (avg) = 0.806531 (all), 0.789670 (pos), 0.822838 (neg) | |
| data reader: epoch = 0, batch = 846 / 4040 | |
| iter = 846, cls_loss (cur) = 0.358887, cls_loss (avg) = 0.411511, lr = 0.010000 | |
| iter = 846, accuracy (cur) = 0.880000 (all), 0.894737 (pos), 0.870968 (neg) | |
| iter = 846, accuracy (avg) = 0.807266 (all), 0.790721 (pos), 0.823319 (neg) | |
| data reader: epoch = 0, batch = 847 / 4040 | |
| iter = 847, cls_loss (cur) = 0.469031, cls_loss (avg) = 0.412086, lr = 0.010000 | |
| iter = 847, accuracy (cur) = 0.800000 (all), 0.764706 (pos), 0.818182 (neg) | |
| iter = 847, accuracy (avg) = 0.807193 (all), 0.790461 (pos), 0.823268 (neg) | |
| data reader: epoch = 0, batch = 848 / 4040 | |
| iter = 848, cls_loss (cur) = 0.321596, cls_loss (avg) = 0.411181, lr = 0.010000 | |
| iter = 848, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.950000 (neg) | |
| iter = 848, accuracy (avg) = 0.807721 (all), 0.790556 (pos), 0.824535 (neg) | |
| data reader: epoch = 0, batch = 849 / 4040 | |
| iter = 849, cls_loss (cur) = 0.655927, cls_loss (avg) = 0.413629, lr = 0.010000 | |
| iter = 849, accuracy (cur) = 0.720000 (all), 0.541667 (pos), 0.884615 (neg) | |
| iter = 849, accuracy (avg) = 0.806844 (all), 0.788067 (pos), 0.825136 (neg) | |
| data reader: epoch = 0, batch = 850 / 4040 | |
| iter = 850, cls_loss (cur) = 0.381538, cls_loss (avg) = 0.413308, lr = 0.010000 | |
| iter = 850, accuracy (cur) = 0.840000 (all), 0.741935 (pos), 1.000000 (neg) | |
| iter = 850, accuracy (avg) = 0.807176 (all), 0.787606 (pos), 0.826884 (neg) | |
| data reader: epoch = 0, batch = 851 / 4040 | |
| iter = 851, cls_loss (cur) = 0.425208, cls_loss (avg) = 0.413427, lr = 0.010000 | |
| iter = 851, accuracy (cur) = 0.760000 (all), 0.653846 (pos), 0.875000 (neg) | |
| iter = 851, accuracy (avg) = 0.806704 (all), 0.786268 (pos), 0.827365 (neg) | |
| data reader: epoch = 0, batch = 852 / 4040 | |
| iter = 852, cls_loss (cur) = 0.386478, cls_loss (avg) = 0.413157, lr = 0.010000 | |
| iter = 852, accuracy (cur) = 0.760000 (all), 0.807692 (pos), 0.708333 (neg) | |
| iter = 852, accuracy (avg) = 0.806237 (all), 0.786483 (pos), 0.826175 (neg) | |
| data reader: epoch = 0, batch = 853 / 4040 | |
| iter = 853, cls_loss (cur) = 0.393504, cls_loss (avg) = 0.412961, lr = 0.010000 | |
| iter = 853, accuracy (cur) = 0.780000 (all), 0.806452 (pos), 0.736842 (neg) | |
| iter = 853, accuracy (avg) = 0.805974 (all), 0.786682 (pos), 0.825282 (neg) | |
| data reader: epoch = 0, batch = 854 / 4040 | |
| iter = 854, cls_loss (cur) = 0.360330, cls_loss (avg) = 0.412434, lr = 0.010000 | |
| iter = 854, accuracy (cur) = 0.840000 (all), 0.958333 (pos), 0.730769 (neg) | |
| iter = 854, accuracy (avg) = 0.806315 (all), 0.788399 (pos), 0.824337 (neg) | |
| data reader: epoch = 0, batch = 855 / 4040 | |
| iter = 855, cls_loss (cur) = 0.329578, cls_loss (avg) = 0.411606, lr = 0.010000 | |
| iter = 855, accuracy (cur) = 0.880000 (all), 0.964286 (pos), 0.772727 (neg) | |
| iter = 855, accuracy (avg) = 0.807052 (all), 0.790158 (pos), 0.823821 (neg) | |
| data reader: epoch = 0, batch = 856 / 4040 | |
| iter = 856, cls_loss (cur) = 0.354429, cls_loss (avg) = 0.411034, lr = 0.010000 | |
| iter = 856, accuracy (cur) = 0.900000 (all), 0.958333 (pos), 0.846154 (neg) | |
| iter = 856, accuracy (avg) = 0.807981 (all), 0.791839 (pos), 0.824044 (neg) | |
| data reader: epoch = 0, batch = 857 / 4040 | |
| iter = 857, cls_loss (cur) = 0.467287, cls_loss (avg) = 0.411597, lr = 0.010000 | |
| iter = 857, accuracy (cur) = 0.820000 (all), 0.892857 (pos), 0.727273 (neg) | |
| iter = 857, accuracy (avg) = 0.808101 (all), 0.792850 (pos), 0.823076 (neg) | |
| data reader: epoch = 0, batch = 858 / 4040 | |
| iter = 858, cls_loss (cur) = 0.339996, cls_loss (avg) = 0.410881, lr = 0.010000 | |
| iter = 858, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 858, accuracy (avg) = 0.808420 (all), 0.793767 (pos), 0.822762 (neg) | |
| data reader: epoch = 0, batch = 859 / 4040 | |
| iter = 859, cls_loss (cur) = 0.512593, cls_loss (avg) = 0.411898, lr = 0.010000 | |
| iter = 859, accuracy (cur) = 0.700000 (all), 0.708333 (pos), 0.692308 (neg) | |
| iter = 859, accuracy (avg) = 0.807336 (all), 0.792913 (pos), 0.821458 (neg) | |
| data reader: epoch = 0, batch = 860 / 4040 | |
| iter = 860, cls_loss (cur) = 0.315281, cls_loss (avg) = 0.410932, lr = 0.010000 | |
| iter = 860, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 860, accuracy (avg) = 0.808063 (all), 0.793620 (pos), 0.822172 (neg) | |
| data reader: epoch = 0, batch = 861 / 4040 | |
| iter = 861, cls_loss (cur) = 0.416201, cls_loss (avg) = 0.410984, lr = 0.010000 | |
| iter = 861, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 861, accuracy (avg) = 0.807582 (all), 0.792084 (pos), 0.822750 (neg) | |
| data reader: epoch = 0, batch = 862 / 4040 | |
| iter = 862, cls_loss (cur) = 0.463851, cls_loss (avg) = 0.411513, lr = 0.010000 | |
| iter = 862, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.900000 (neg) | |
| iter = 862, accuracy (avg) = 0.807106 (all), 0.790830 (pos), 0.823522 (neg) | |
| data reader: epoch = 0, batch = 863 / 4040 | |
| iter = 863, cls_loss (cur) = 0.351442, cls_loss (avg) = 0.410912, lr = 0.010000 | |
| iter = 863, accuracy (cur) = 0.860000 (all), 0.900000 (pos), 0.833333 (neg) | |
| iter = 863, accuracy (avg) = 0.807635 (all), 0.791921 (pos), 0.823620 (neg) | |
| data reader: epoch = 0, batch = 864 / 4040 | |
| iter = 864, cls_loss (cur) = 0.344409, cls_loss (avg) = 0.410247, lr = 0.010000 | |
| iter = 864, accuracy (cur) = 0.840000 (all), 0.739130 (pos), 0.925926 (neg) | |
| iter = 864, accuracy (avg) = 0.807959 (all), 0.791394 (pos), 0.824644 (neg) | |
| data reader: epoch = 0, batch = 865 / 4040 | |
| iter = 865, cls_loss (cur) = 0.347454, cls_loss (avg) = 0.409619, lr = 0.010000 | |
| iter = 865, accuracy (cur) = 0.820000 (all), 0.739130 (pos), 0.888889 (neg) | |
| iter = 865, accuracy (avg) = 0.808079 (all), 0.790871 (pos), 0.825286 (neg) | |
| data reader: epoch = 0, batch = 866 / 4040 | |
| iter = 866, cls_loss (cur) = 0.278206, cls_loss (avg) = 0.408305, lr = 0.010000 | |
| iter = 866, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 866, accuracy (avg) = 0.808998 (all), 0.791851 (pos), 0.826164 (neg) | |
| data reader: epoch = 0, batch = 867 / 4040 | |
| iter = 867, cls_loss (cur) = 0.357941, cls_loss (avg) = 0.407801, lr = 0.010000 | |
| iter = 867, accuracy (cur) = 0.780000 (all), 0.714286 (pos), 0.863636 (neg) | |
| iter = 867, accuracy (avg) = 0.808708 (all), 0.791075 (pos), 0.826538 (neg) | |
| data reader: epoch = 0, batch = 868 / 4040 | |
| iter = 868, cls_loss (cur) = 0.311708, cls_loss (avg) = 0.406841, lr = 0.010000 | |
| iter = 868, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 868, accuracy (avg) = 0.809621 (all), 0.792365 (pos), 0.827073 (neg) | |
| data reader: epoch = 0, batch = 869 / 4040 | |
| iter = 869, cls_loss (cur) = 0.395631, cls_loss (avg) = 0.406728, lr = 0.010000 | |
| iter = 869, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 869, accuracy (avg) = 0.809725 (all), 0.792903 (pos), 0.826719 (neg) | |
| data reader: epoch = 0, batch = 870 / 4040 | |
| iter = 870, cls_loss (cur) = 0.408413, cls_loss (avg) = 0.406745, lr = 0.010000 | |
| iter = 870, accuracy (cur) = 0.800000 (all), 0.909091 (pos), 0.714286 (neg) | |
| iter = 870, accuracy (avg) = 0.809628 (all), 0.794064 (pos), 0.825595 (neg) | |
| data reader: epoch = 0, batch = 871 / 4040 | |
| iter = 871, cls_loss (cur) = 0.383366, cls_loss (avg) = 0.406511, lr = 0.010000 | |
| iter = 871, accuracy (cur) = 0.860000 (all), 0.884615 (pos), 0.833333 (neg) | |
| iter = 871, accuracy (avg) = 0.810132 (all), 0.794970 (pos), 0.825672 (neg) | |
| data reader: epoch = 0, batch = 872 / 4040 | |
| iter = 872, cls_loss (cur) = 0.385275, cls_loss (avg) = 0.406299, lr = 0.010000 | |
| iter = 872, accuracy (cur) = 0.820000 (all), 0.722222 (pos), 0.875000 (neg) | |
| iter = 872, accuracy (avg) = 0.810230 (all), 0.794243 (pos), 0.826165 (neg) | |
| data reader: epoch = 0, batch = 873 / 4040 | |
| iter = 873, cls_loss (cur) = 0.343345, cls_loss (avg) = 0.405670, lr = 0.010000 | |
| iter = 873, accuracy (cur) = 0.840000 (all), 0.916667 (pos), 0.769231 (neg) | |
| iter = 873, accuracy (avg) = 0.810528 (all), 0.795467 (pos), 0.825596 (neg) | |
| data reader: epoch = 0, batch = 874 / 4040 | |
| iter = 874, cls_loss (cur) = 0.350973, cls_loss (avg) = 0.405123, lr = 0.010000 | |
| iter = 874, accuracy (cur) = 0.880000 (all), 0.956522 (pos), 0.814815 (neg) | |
| iter = 874, accuracy (avg) = 0.811223 (all), 0.797077 (pos), 0.825488 (neg) | |
| data reader: epoch = 0, batch = 875 / 4040 | |
| iter = 875, cls_loss (cur) = 0.347822, cls_loss (avg) = 0.404550, lr = 0.010000 | |
| iter = 875, accuracy (cur) = 0.900000 (all), 0.827586 (pos), 1.000000 (neg) | |
| iter = 875, accuracy (avg) = 0.812110 (all), 0.797382 (pos), 0.827233 (neg) | |
| data reader: epoch = 0, batch = 876 / 4040 | |
| iter = 876, cls_loss (cur) = 0.347760, cls_loss (avg) = 0.403982, lr = 0.010000 | |
| iter = 876, accuracy (cur) = 0.800000 (all), 0.666667 (pos), 0.956522 (neg) | |
| iter = 876, accuracy (avg) = 0.811989 (all), 0.796075 (pos), 0.828526 (neg) | |
| data reader: epoch = 0, batch = 877 / 4040 | |
| iter = 877, cls_loss (cur) = 0.408496, cls_loss (avg) = 0.404027, lr = 0.010000 | |
| iter = 877, accuracy (cur) = 0.760000 (all), 0.636364 (pos), 0.857143 (neg) | |
| iter = 877, accuracy (avg) = 0.811469 (all), 0.794478 (pos), 0.828812 (neg) | |
| data reader: epoch = 0, batch = 878 / 4040 | |
| iter = 878, cls_loss (cur) = 0.357128, cls_loss (avg) = 0.403558, lr = 0.010000 | |
| iter = 878, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 878, accuracy (avg) = 0.812155 (all), 0.795733 (pos), 0.828924 (neg) | |
| data reader: epoch = 0, batch = 879 / 4040 | |
| iter = 879, cls_loss (cur) = 0.464545, cls_loss (avg) = 0.404168, lr = 0.010000 | |
| iter = 879, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 879, accuracy (avg) = 0.811633 (all), 0.794813 (pos), 0.828896 (neg) | |
| data reader: epoch = 0, batch = 880 / 4040 | |
| iter = 880, cls_loss (cur) = 0.441451, cls_loss (avg) = 0.404541, lr = 0.010000 | |
| iter = 880, accuracy (cur) = 0.760000 (all), 0.880000 (pos), 0.640000 (neg) | |
| iter = 880, accuracy (avg) = 0.811117 (all), 0.795665 (pos), 0.827007 (neg) | |
| data reader: epoch = 0, batch = 881 / 4040 | |
| iter = 881, cls_loss (cur) = 0.355858, cls_loss (avg) = 0.404054, lr = 0.010000 | |
| iter = 881, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 881, accuracy (avg) = 0.811206 (all), 0.795534 (pos), 0.827255 (neg) | |
| data reader: epoch = 0, batch = 882 / 4040 | |
| iter = 882, cls_loss (cur) = 0.384307, cls_loss (avg) = 0.403856, lr = 0.010000 | |
| iter = 882, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 882, accuracy (avg) = 0.811694 (all), 0.795579 (pos), 0.828183 (neg) | |
| data reader: epoch = 0, batch = 883 / 4040 | |
| iter = 883, cls_loss (cur) = 0.439409, cls_loss (avg) = 0.404212, lr = 0.010000 | |
| iter = 883, accuracy (cur) = 0.740000 (all), 0.709677 (pos), 0.789474 (neg) | |
| iter = 883, accuracy (avg) = 0.810977 (all), 0.794720 (pos), 0.827796 (neg) | |
| data reader: epoch = 0, batch = 884 / 4040 | |
| iter = 884, cls_loss (cur) = 0.368011, cls_loss (avg) = 0.403850, lr = 0.010000 | |
| iter = 884, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 884, accuracy (avg) = 0.811067 (all), 0.795106 (pos), 0.827595 (neg) | |
| data reader: epoch = 0, batch = 885 / 4040 | |
| iter = 885, cls_loss (cur) = 0.316808, cls_loss (avg) = 0.402979, lr = 0.010000 | |
| iter = 885, accuracy (cur) = 0.860000 (all), 0.818182 (pos), 0.892857 (neg) | |
| iter = 885, accuracy (avg) = 0.811556 (all), 0.795337 (pos), 0.828247 (neg) | |
| data reader: epoch = 0, batch = 886 / 4040 | |
| iter = 886, cls_loss (cur) = 0.326564, cls_loss (avg) = 0.402215, lr = 0.010000 | |
| iter = 886, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 886, accuracy (avg) = 0.812241 (all), 0.796514 (pos), 0.828483 (neg) | |
| data reader: epoch = 0, batch = 887 / 4040 | |
| iter = 887, cls_loss (cur) = 0.490222, cls_loss (avg) = 0.403095, lr = 0.010000 | |
| iter = 887, accuracy (cur) = 0.740000 (all), 0.730769 (pos), 0.750000 (neg) | |
| iter = 887, accuracy (avg) = 0.811518 (all), 0.795857 (pos), 0.827698 (neg) | |
| data reader: epoch = 0, batch = 888 / 4040 | |
| iter = 888, cls_loss (cur) = 0.385108, cls_loss (avg) = 0.402915, lr = 0.010000 | |
| iter = 888, accuracy (cur) = 0.840000 (all), 0.931034 (pos), 0.714286 (neg) | |
| iter = 888, accuracy (avg) = 0.811803 (all), 0.797208 (pos), 0.826564 (neg) | |
| data reader: epoch = 0, batch = 889 / 4040 | |
| iter = 889, cls_loss (cur) = 0.352562, cls_loss (avg) = 0.402412, lr = 0.010000 | |
| iter = 889, accuracy (cur) = 0.840000 (all), 0.958333 (pos), 0.730769 (neg) | |
| iter = 889, accuracy (avg) = 0.812085 (all), 0.798820 (pos), 0.825606 (neg) | |
| data reader: epoch = 0, batch = 890 / 4040 | |
| iter = 890, cls_loss (cur) = 0.297315, cls_loss (avg) = 0.401361, lr = 0.010000 | |
| iter = 890, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.923077 (neg) | |
| iter = 890, accuracy (avg) = 0.812764 (all), 0.799165 (pos), 0.826581 (neg) | |
| data reader: epoch = 0, batch = 891 / 4040 | |
| iter = 891, cls_loss (cur) = 0.375034, cls_loss (avg) = 0.401098, lr = 0.010000 | |
| iter = 891, accuracy (cur) = 0.880000 (all), 0.869565 (pos), 0.888889 (neg) | |
| iter = 891, accuracy (avg) = 0.813437 (all), 0.799869 (pos), 0.827204 (neg) | |
| data reader: epoch = 0, batch = 892 / 4040 | |
| iter = 892, cls_loss (cur) = 0.300672, cls_loss (avg) = 0.400093, lr = 0.010000 | |
| iter = 892, accuracy (cur) = 0.900000 (all), 0.833333 (pos), 0.961538 (neg) | |
| iter = 892, accuracy (avg) = 0.814302 (all), 0.800203 (pos), 0.828547 (neg) | |
| data reader: epoch = 0, batch = 893 / 4040 | |
| iter = 893, cls_loss (cur) = 0.413223, cls_loss (avg) = 0.400225, lr = 0.010000 | |
| iter = 893, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 893, accuracy (avg) = 0.814359 (all), 0.800416 (pos), 0.828444 (neg) | |
| data reader: epoch = 0, batch = 894 / 4040 | |
| iter = 894, cls_loss (cur) = 0.390934, cls_loss (avg) = 0.400132, lr = 0.010000 | |
| iter = 894, accuracy (cur) = 0.780000 (all), 0.727273 (pos), 0.821429 (neg) | |
| iter = 894, accuracy (avg) = 0.814016 (all), 0.799684 (pos), 0.828374 (neg) | |
| data reader: epoch = 0, batch = 895 / 4040 | |
| iter = 895, cls_loss (cur) = 0.382550, cls_loss (avg) = 0.399956, lr = 0.010000 | |
| iter = 895, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 895, accuracy (avg) = 0.813875 (all), 0.799687 (pos), 0.828090 (neg) | |
| data reader: epoch = 0, batch = 896 / 4040 | |
| iter = 896, cls_loss (cur) = 0.394760, cls_loss (avg) = 0.399904, lr = 0.010000 | |
| iter = 896, accuracy (cur) = 0.820000 (all), 0.900000 (pos), 0.766667 (neg) | |
| iter = 896, accuracy (avg) = 0.813937 (all), 0.800690 (pos), 0.827476 (neg) | |
| data reader: epoch = 0, batch = 897 / 4040 | |
| iter = 897, cls_loss (cur) = 0.381609, cls_loss (avg) = 0.399721, lr = 0.010000 | |
| iter = 897, accuracy (cur) = 0.820000 (all), 0.884615 (pos), 0.750000 (neg) | |
| iter = 897, accuracy (avg) = 0.813997 (all), 0.801530 (pos), 0.826701 (neg) | |
| data reader: epoch = 0, batch = 898 / 4040 | |
| iter = 898, cls_loss (cur) = 0.444182, cls_loss (avg) = 0.400166, lr = 0.010000 | |
| iter = 898, accuracy (cur) = 0.760000 (all), 0.741935 (pos), 0.789474 (neg) | |
| iter = 898, accuracy (avg) = 0.813457 (all), 0.800934 (pos), 0.826329 (neg) | |
| data reader: epoch = 0, batch = 899 / 4040 | |
| iter = 899, cls_loss (cur) = 0.430271, cls_loss (avg) = 0.400467, lr = 0.010000 | |
| iter = 899, accuracy (cur) = 0.820000 (all), 0.842105 (pos), 0.806452 (neg) | |
| iter = 899, accuracy (avg) = 0.813523 (all), 0.801345 (pos), 0.826130 (neg) | |
| data reader: epoch = 0, batch = 900 / 4040 | |
| iter = 900, cls_loss (cur) = 0.365468, cls_loss (avg) = 0.400117, lr = 0.010000 | |
| iter = 900, accuracy (cur) = 0.920000 (all), 0.964286 (pos), 0.863636 (neg) | |
| iter = 900, accuracy (avg) = 0.814588 (all), 0.802975 (pos), 0.826505 (neg) | |
| data reader: epoch = 0, batch = 901 / 4040 | |
| iter = 901, cls_loss (cur) = 0.379007, cls_loss (avg) = 0.399906, lr = 0.010000 | |
| iter = 901, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 901, accuracy (avg) = 0.814442 (all), 0.803127 (pos), 0.826097 (neg) | |
| data reader: epoch = 0, batch = 902 / 4040 | |
| iter = 902, cls_loss (cur) = 0.330915, cls_loss (avg) = 0.399216, lr = 0.010000 | |
| iter = 902, accuracy (cur) = 0.880000 (all), 0.900000 (pos), 0.850000 (neg) | |
| iter = 902, accuracy (avg) = 0.815097 (all), 0.804096 (pos), 0.826336 (neg) | |
| data reader: epoch = 0, batch = 903 / 4040 | |
| iter = 903, cls_loss (cur) = 0.386000, cls_loss (avg) = 0.399084, lr = 0.010000 | |
| iter = 903, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 903, accuracy (avg) = 0.815746 (all), 0.804691 (pos), 0.827001 (neg) | |
| data reader: epoch = 0, batch = 904 / 4040 | |
| iter = 904, cls_loss (cur) = 0.340153, cls_loss (avg) = 0.398494, lr = 0.010000 | |
| iter = 904, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 904, accuracy (avg) = 0.816389 (all), 0.804826 (pos), 0.828017 (neg) | |
| data reader: epoch = 0, batch = 905 / 4040 | |
| iter = 905, cls_loss (cur) = 0.392754, cls_loss (avg) = 0.398437, lr = 0.010000 | |
| iter = 905, accuracy (cur) = 0.800000 (all), 0.652174 (pos), 0.925926 (neg) | |
| iter = 905, accuracy (avg) = 0.816225 (all), 0.803299 (pos), 0.828996 (neg) | |
| data reader: epoch = 0, batch = 906 / 4040 | |
| iter = 906, cls_loss (cur) = 0.296035, cls_loss (avg) = 0.397413, lr = 0.010000 | |
| iter = 906, accuracy (cur) = 0.920000 (all), 0.888889 (pos), 0.956522 (neg) | |
| iter = 906, accuracy (avg) = 0.817263 (all), 0.804155 (pos), 0.830271 (neg) | |
| data reader: epoch = 0, batch = 907 / 4040 | |
| iter = 907, cls_loss (cur) = 0.457452, cls_loss (avg) = 0.398013, lr = 0.010000 | |
| iter = 907, accuracy (cur) = 0.720000 (all), 0.578947 (pos), 0.806452 (neg) | |
| iter = 907, accuracy (avg) = 0.816290 (all), 0.801903 (pos), 0.830033 (neg) | |
| data reader: epoch = 0, batch = 908 / 4040 | |
| iter = 908, cls_loss (cur) = 0.396702, cls_loss (avg) = 0.398000, lr = 0.010000 | |
| iter = 908, accuracy (cur) = 0.820000 (all), 0.842105 (pos), 0.806452 (neg) | |
| iter = 908, accuracy (avg) = 0.816327 (all), 0.802305 (pos), 0.829797 (neg) | |
| data reader: epoch = 0, batch = 909 / 4040 | |
| iter = 909, cls_loss (cur) = 0.372269, cls_loss (avg) = 0.397743, lr = 0.010000 | |
| iter = 909, accuracy (cur) = 0.820000 (all), 0.619048 (pos), 0.965517 (neg) | |
| iter = 909, accuracy (avg) = 0.816364 (all), 0.800473 (pos), 0.831154 (neg) | |
| data reader: epoch = 0, batch = 910 / 4040 | |
| iter = 910, cls_loss (cur) = 0.437205, cls_loss (avg) = 0.398137, lr = 0.010000 | |
| iter = 910, accuracy (cur) = 0.780000 (all), 0.806452 (pos), 0.736842 (neg) | |
| iter = 910, accuracy (avg) = 0.816000 (all), 0.800533 (pos), 0.830211 (neg) | |
| data reader: epoch = 0, batch = 911 / 4040 | |
| iter = 911, cls_loss (cur) = 0.390748, cls_loss (avg) = 0.398064, lr = 0.010000 | |
| iter = 911, accuracy (cur) = 0.820000 (all), 0.880000 (pos), 0.760000 (neg) | |
| iter = 911, accuracy (avg) = 0.816040 (all), 0.801327 (pos), 0.829509 (neg) | |
| data reader: epoch = 0, batch = 912 / 4040 | |
| iter = 912, cls_loss (cur) = 0.495692, cls_loss (avg) = 0.399040, lr = 0.010000 | |
| iter = 912, accuracy (cur) = 0.760000 (all), 0.740741 (pos), 0.782609 (neg) | |
| iter = 912, accuracy (avg) = 0.815480 (all), 0.800721 (pos), 0.829040 (neg) | |
| data reader: epoch = 0, batch = 913 / 4040 | |
| iter = 913, cls_loss (cur) = 0.497580, cls_loss (avg) = 0.400025, lr = 0.010000 | |
| iter = 913, accuracy (cur) = 0.780000 (all), 0.833333 (pos), 0.750000 (neg) | |
| iter = 913, accuracy (avg) = 0.815125 (all), 0.801047 (pos), 0.828250 (neg) | |
| data reader: epoch = 0, batch = 914 / 4040 | |
| iter = 914, cls_loss (cur) = 0.486088, cls_loss (avg) = 0.400886, lr = 0.010000 | |
| iter = 914, accuracy (cur) = 0.720000 (all), 0.681818 (pos), 0.750000 (neg) | |
| iter = 914, accuracy (avg) = 0.814174 (all), 0.799855 (pos), 0.827467 (neg) | |
| data reader: epoch = 0, batch = 915 / 4040 | |
| iter = 915, cls_loss (cur) = 0.347411, cls_loss (avg) = 0.400351, lr = 0.010000 | |
| iter = 915, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 915, accuracy (avg) = 0.814832 (all), 0.800038 (pos), 0.828478 (neg) | |
| data reader: epoch = 0, batch = 916 / 4040 | |
| iter = 916, cls_loss (cur) = 0.403087, cls_loss (avg) = 0.400378, lr = 0.010000 | |
| iter = 916, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.909091 (neg) | |
| iter = 916, accuracy (avg) = 0.814884 (all), 0.799538 (pos), 0.829285 (neg) | |
| data reader: epoch = 0, batch = 917 / 4040 | |
| iter = 917, cls_loss (cur) = 0.357598, cls_loss (avg) = 0.399951, lr = 0.010000 | |
| iter = 917, accuracy (cur) = 0.860000 (all), 0.833333 (pos), 0.884615 (neg) | |
| iter = 917, accuracy (avg) = 0.815335 (all), 0.799876 (pos), 0.829838 (neg) | |
| data reader: epoch = 0, batch = 918 / 4040 | |
| iter = 918, cls_loss (cur) = 0.297391, cls_loss (avg) = 0.398925, lr = 0.010000 | |
| iter = 918, accuracy (cur) = 0.920000 (all), 0.884615 (pos), 0.958333 (neg) | |
| iter = 918, accuracy (avg) = 0.816382 (all), 0.800723 (pos), 0.831123 (neg) | |
| data reader: epoch = 0, batch = 919 / 4040 | |
| iter = 919, cls_loss (cur) = 0.342118, cls_loss (avg) = 0.398357, lr = 0.010000 | |
| iter = 919, accuracy (cur) = 0.820000 (all), 0.884615 (pos), 0.750000 (neg) | |
| iter = 919, accuracy (avg) = 0.816418 (all), 0.801562 (pos), 0.830312 (neg) | |
| data reader: epoch = 0, batch = 920 / 4040 | |
| iter = 920, cls_loss (cur) = 0.430883, cls_loss (avg) = 0.398682, lr = 0.010000 | |
| iter = 920, accuracy (cur) = 0.760000 (all), 0.904762 (pos), 0.655172 (neg) | |
| iter = 920, accuracy (avg) = 0.815854 (all), 0.802594 (pos), 0.828560 (neg) | |
| data reader: epoch = 0, batch = 921 / 4040 | |
| iter = 921, cls_loss (cur) = 0.320387, cls_loss (avg) = 0.397899, lr = 0.010000 | |
| iter = 921, accuracy (cur) = 0.880000 (all), 0.962963 (pos), 0.782609 (neg) | |
| iter = 921, accuracy (avg) = 0.816495 (all), 0.804198 (pos), 0.828101 (neg) | |
| data reader: epoch = 0, batch = 922 / 4040 | |
| iter = 922, cls_loss (cur) = 0.394431, cls_loss (avg) = 0.397865, lr = 0.010000 | |
| iter = 922, accuracy (cur) = 0.740000 (all), 0.821429 (pos), 0.636364 (neg) | |
| iter = 922, accuracy (avg) = 0.815730 (all), 0.804370 (pos), 0.826183 (neg) | |
| data reader: epoch = 0, batch = 923 / 4040 | |
| iter = 923, cls_loss (cur) = 0.425217, cls_loss (avg) = 0.398138, lr = 0.010000 | |
| iter = 923, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.818182 (neg) | |
| iter = 923, accuracy (avg) = 0.815373 (all), 0.803827 (pos), 0.826103 (neg) | |
| data reader: epoch = 0, batch = 924 / 4040 | |
| iter = 924, cls_loss (cur) = 0.356817, cls_loss (avg) = 0.397725, lr = 0.010000 | |
| iter = 924, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.857143 (neg) | |
| iter = 924, accuracy (avg) = 0.816019 (all), 0.804879 (pos), 0.826414 (neg) | |
| data reader: epoch = 0, batch = 925 / 4040 | |
| iter = 925, cls_loss (cur) = 0.439838, cls_loss (avg) = 0.398146, lr = 0.010000 | |
| iter = 925, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 925, accuracy (avg) = 0.816659 (all), 0.805012 (pos), 0.827435 (neg) | |
| data reader: epoch = 0, batch = 926 / 4040 | |
| iter = 926, cls_loss (cur) = 0.296769, cls_loss (avg) = 0.397132, lr = 0.010000 | |
| iter = 926, accuracy (cur) = 0.880000 (all), 0.827586 (pos), 0.952381 (neg) | |
| iter = 926, accuracy (avg) = 0.817292 (all), 0.805238 (pos), 0.828685 (neg) | |
| data reader: epoch = 0, batch = 927 / 4040 | |
| iter = 927, cls_loss (cur) = 0.388303, cls_loss (avg) = 0.397044, lr = 0.010000 | |
| iter = 927, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.840000 (neg) | |
| iter = 927, accuracy (avg) = 0.817319 (all), 0.805186 (pos), 0.828798 (neg) | |
| data reader: epoch = 0, batch = 928 / 4040 | |
| iter = 928, cls_loss (cur) = 0.422251, cls_loss (avg) = 0.397296, lr = 0.010000 | |
| iter = 928, accuracy (cur) = 0.760000 (all), 0.842105 (pos), 0.709677 (neg) | |
| iter = 928, accuracy (avg) = 0.816746 (all), 0.805555 (pos), 0.827607 (neg) | |
| data reader: epoch = 0, batch = 929 / 4040 | |
| iter = 929, cls_loss (cur) = 0.361382, cls_loss (avg) = 0.396937, lr = 0.010000 | |
| iter = 929, accuracy (cur) = 0.780000 (all), 0.869565 (pos), 0.703704 (neg) | |
| iter = 929, accuracy (avg) = 0.816379 (all), 0.806195 (pos), 0.826368 (neg) | |
| data reader: epoch = 0, batch = 930 / 4040 | |
| iter = 930, cls_loss (cur) = 0.529567, cls_loss (avg) = 0.398263, lr = 0.010000 | |
| iter = 930, accuracy (cur) = 0.720000 (all), 0.666667 (pos), 0.782609 (neg) | |
| iter = 930, accuracy (avg) = 0.815415 (all), 0.804800 (pos), 0.825930 (neg) | |
| data reader: epoch = 0, batch = 931 / 4040 | |
| iter = 931, cls_loss (cur) = 0.365019, cls_loss (avg) = 0.397931, lr = 0.010000 | |
| iter = 931, accuracy (cur) = 0.820000 (all), 0.823529 (pos), 0.812500 (neg) | |
| iter = 931, accuracy (avg) = 0.815461 (all), 0.804987 (pos), 0.825796 (neg) | |
| data reader: epoch = 0, batch = 932 / 4040 | |
| iter = 932, cls_loss (cur) = 0.339951, cls_loss (avg) = 0.397351, lr = 0.010000 | |
| iter = 932, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 932, accuracy (avg) = 0.815706 (all), 0.805399 (pos), 0.825871 (neg) | |
| data reader: epoch = 0, batch = 933 / 4040 | |
| iter = 933, cls_loss (cur) = 0.332455, cls_loss (avg) = 0.396702, lr = 0.010000 | |
| iter = 933, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 933, accuracy (avg) = 0.816349 (all), 0.806145 (pos), 0.826412 (neg) | |
| data reader: epoch = 0, batch = 934 / 4040 | |
| iter = 934, cls_loss (cur) = 0.336575, cls_loss (avg) = 0.396101, lr = 0.010000 | |
| iter = 934, accuracy (cur) = 0.900000 (all), 1.000000 (pos), 0.772727 (neg) | |
| iter = 934, accuracy (avg) = 0.817186 (all), 0.808083 (pos), 0.825876 (neg) | |
| data reader: epoch = 0, batch = 935 / 4040 | |
| iter = 935, cls_loss (cur) = 0.430220, cls_loss (avg) = 0.396442, lr = 0.010000 | |
| iter = 935, accuracy (cur) = 0.820000 (all), 0.875000 (pos), 0.769231 (neg) | |
| iter = 935, accuracy (avg) = 0.817214 (all), 0.808752 (pos), 0.825309 (neg) | |
| data reader: epoch = 0, batch = 936 / 4040 | |
| iter = 936, cls_loss (cur) = 0.449376, cls_loss (avg) = 0.396971, lr = 0.010000 | |
| iter = 936, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.781250 (neg) | |
| iter = 936, accuracy (avg) = 0.817042 (all), 0.808998 (pos), 0.824868 (neg) | |
| data reader: epoch = 0, batch = 937 / 4040 | |
| iter = 937, cls_loss (cur) = 0.374196, cls_loss (avg) = 0.396744, lr = 0.010000 | |
| iter = 937, accuracy (cur) = 0.860000 (all), 0.894737 (pos), 0.838710 (neg) | |
| iter = 937, accuracy (avg) = 0.817471 (all), 0.809856 (pos), 0.825007 (neg) | |
| data reader: epoch = 0, batch = 938 / 4040 | |
| iter = 938, cls_loss (cur) = 0.420449, cls_loss (avg) = 0.396981, lr = 0.010000 | |
| iter = 938, accuracy (cur) = 0.820000 (all), 0.869565 (pos), 0.777778 (neg) | |
| iter = 938, accuracy (avg) = 0.817496 (all), 0.810453 (pos), 0.824535 (neg) | |
| data reader: epoch = 0, batch = 939 / 4040 | |
| iter = 939, cls_loss (cur) = 0.400460, cls_loss (avg) = 0.397015, lr = 0.010000 | |
| iter = 939, accuracy (cur) = 0.840000 (all), 0.900000 (pos), 0.800000 (neg) | |
| iter = 939, accuracy (avg) = 0.817722 (all), 0.811348 (pos), 0.824289 (neg) | |
| data reader: epoch = 0, batch = 940 / 4040 | |
| iter = 940, cls_loss (cur) = 0.336919, cls_loss (avg) = 0.396414, lr = 0.010000 | |
| iter = 940, accuracy (cur) = 0.840000 (all), 0.760000 (pos), 0.920000 (neg) | |
| iter = 940, accuracy (avg) = 0.817944 (all), 0.810835 (pos), 0.825246 (neg) | |
| data reader: epoch = 0, batch = 941 / 4040 | |
| iter = 941, cls_loss (cur) = 0.424406, cls_loss (avg) = 0.396694, lr = 0.010000 | |
| iter = 941, accuracy (cur) = 0.860000 (all), 0.777778 (pos), 0.906250 (neg) | |
| iter = 941, accuracy (avg) = 0.818365 (all), 0.810504 (pos), 0.826056 (neg) | |
| data reader: epoch = 0, batch = 942 / 4040 | |
| iter = 942, cls_loss (cur) = 0.395647, cls_loss (avg) = 0.396684, lr = 0.010000 | |
| iter = 942, accuracy (cur) = 0.760000 (all), 0.619048 (pos), 0.862069 (neg) | |
| iter = 942, accuracy (avg) = 0.817781 (all), 0.808589 (pos), 0.826417 (neg) | |
| data reader: epoch = 0, batch = 943 / 4040 | |
| iter = 943, cls_loss (cur) = 0.435817, cls_loss (avg) = 0.397075, lr = 0.010000 | |
| iter = 943, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 943, accuracy (avg) = 0.817403 (all), 0.807811 (pos), 0.826486 (neg) | |
| data reader: epoch = 0, batch = 944 / 4040 | |
| iter = 944, cls_loss (cur) = 0.344624, cls_loss (avg) = 0.396551, lr = 0.010000 | |
| iter = 944, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.923077 (neg) | |
| iter = 944, accuracy (avg) = 0.817629 (all), 0.807233 (pos), 0.827452 (neg) | |
| data reader: epoch = 0, batch = 945 / 4040 | |
| iter = 945, cls_loss (cur) = 0.319550, cls_loss (avg) = 0.395781, lr = 0.010000 | |
| iter = 945, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 945, accuracy (avg) = 0.818053 (all), 0.807622 (pos), 0.827927 (neg) | |
| data reader: epoch = 0, batch = 946 / 4040 | |
| iter = 946, cls_loss (cur) = 0.342087, cls_loss (avg) = 0.395244, lr = 0.010000 | |
| iter = 946, accuracy (cur) = 0.920000 (all), 0.880000 (pos), 0.960000 (neg) | |
| iter = 946, accuracy (avg) = 0.819073 (all), 0.808346 (pos), 0.829248 (neg) | |
| data reader: epoch = 0, batch = 947 / 4040 | |
| iter = 947, cls_loss (cur) = 0.439543, cls_loss (avg) = 0.395687, lr = 0.010000 | |
| iter = 947, accuracy (cur) = 0.760000 (all), 0.700000 (pos), 0.850000 (neg) | |
| iter = 947, accuracy (avg) = 0.818482 (all), 0.807263 (pos), 0.829455 (neg) | |
| data reader: epoch = 0, batch = 948 / 4040 | |
| iter = 948, cls_loss (cur) = 0.309929, cls_loss (avg) = 0.394829, lr = 0.010000 | |
| iter = 948, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 948, accuracy (avg) = 0.818697 (all), 0.807709 (pos), 0.829422 (neg) | |
| data reader: epoch = 0, batch = 949 / 4040 | |
| iter = 949, cls_loss (cur) = 0.354428, cls_loss (avg) = 0.394425, lr = 0.010000 | |
| iter = 949, accuracy (cur) = 0.800000 (all), 0.880000 (pos), 0.720000 (neg) | |
| iter = 949, accuracy (avg) = 0.818510 (all), 0.808431 (pos), 0.828327 (neg) | |
| data reader: epoch = 0, batch = 950 / 4040 | |
| iter = 950, cls_loss (cur) = 0.322077, cls_loss (avg) = 0.393702, lr = 0.010000 | |
| iter = 950, accuracy (cur) = 0.900000 (all), 0.964286 (pos), 0.818182 (neg) | |
| iter = 950, accuracy (avg) = 0.819325 (all), 0.809990 (pos), 0.828226 (neg) | |
| data reader: epoch = 0, batch = 951 / 4040 | |
| iter = 951, cls_loss (cur) = 0.462097, cls_loss (avg) = 0.394386, lr = 0.010000 | |
| iter = 951, accuracy (cur) = 0.800000 (all), 0.894737 (pos), 0.741935 (neg) | |
| iter = 951, accuracy (avg) = 0.819132 (all), 0.810838 (pos), 0.827363 (neg) | |
| data reader: epoch = 0, batch = 952 / 4040 | |
| iter = 952, cls_loss (cur) = 0.296578, cls_loss (avg) = 0.393408, lr = 0.010000 | |
| iter = 952, accuracy (cur) = 0.880000 (all), 0.962963 (pos), 0.782609 (neg) | |
| iter = 952, accuracy (avg) = 0.819740 (all), 0.812359 (pos), 0.826916 (neg) | |
| data reader: epoch = 0, batch = 953 / 4040 | |
| iter = 953, cls_loss (cur) = 0.395624, cls_loss (avg) = 0.393430, lr = 0.010000 | |
| iter = 953, accuracy (cur) = 0.800000 (all), 0.954545 (pos), 0.678571 (neg) | |
| iter = 953, accuracy (avg) = 0.819543 (all), 0.813781 (pos), 0.825432 (neg) | |
| data reader: epoch = 0, batch = 954 / 4040 | |
| iter = 954, cls_loss (cur) = 0.326606, cls_loss (avg) = 0.392761, lr = 0.010000 | |
| iter = 954, accuracy (cur) = 0.800000 (all), 0.769231 (pos), 0.833333 (neg) | |
| iter = 954, accuracy (avg) = 0.819348 (all), 0.813335 (pos), 0.825511 (neg) | |
| data reader: epoch = 0, batch = 955 / 4040 | |
| iter = 955, cls_loss (cur) = 0.532726, cls_loss (avg) = 0.394161, lr = 0.010000 | |
| iter = 955, accuracy (cur) = 0.800000 (all), 0.913043 (pos), 0.703704 (neg) | |
| iter = 955, accuracy (avg) = 0.819154 (all), 0.814332 (pos), 0.824293 (neg) | |
| data reader: epoch = 0, batch = 956 / 4040 | |
| iter = 956, cls_loss (cur) = 0.377048, cls_loss (avg) = 0.393990, lr = 0.010000 | |
| iter = 956, accuracy (cur) = 0.880000 (all), 0.925926 (pos), 0.826087 (neg) | |
| iter = 956, accuracy (avg) = 0.819763 (all), 0.815448 (pos), 0.824311 (neg) | |
| data reader: epoch = 0, batch = 957 / 4040 | |
| iter = 957, cls_loss (cur) = 0.398702, cls_loss (avg) = 0.394037, lr = 0.010000 | |
| iter = 957, accuracy (cur) = 0.820000 (all), 0.652174 (pos), 0.962963 (neg) | |
| iter = 957, accuracy (avg) = 0.819765 (all), 0.813815 (pos), 0.825697 (neg) | |
| data reader: epoch = 0, batch = 958 / 4040 | |
| iter = 958, cls_loss (cur) = 0.441972, cls_loss (avg) = 0.394516, lr = 0.010000 | |
| iter = 958, accuracy (cur) = 0.800000 (all), 0.708333 (pos), 0.884615 (neg) | |
| iter = 958, accuracy (avg) = 0.819567 (all), 0.812761 (pos), 0.826287 (neg) | |
| data reader: epoch = 0, batch = 959 / 4040 | |
| iter = 959, cls_loss (cur) = 0.381630, cls_loss (avg) = 0.394388, lr = 0.010000 | |
| iter = 959, accuracy (cur) = 0.820000 (all), 0.714286 (pos), 0.954545 (neg) | |
| iter = 959, accuracy (avg) = 0.819572 (all), 0.811776 (pos), 0.827569 (neg) | |
| data reader: epoch = 0, batch = 960 / 4040 | |
| iter = 960, cls_loss (cur) = 0.400921, cls_loss (avg) = 0.394453, lr = 0.010000 | |
| iter = 960, accuracy (cur) = 0.800000 (all), 0.733333 (pos), 0.900000 (neg) | |
| iter = 960, accuracy (avg) = 0.819376 (all), 0.810991 (pos), 0.828294 (neg) | |
| data reader: epoch = 0, batch = 961 / 4040 | |
| iter = 961, cls_loss (cur) = 0.579048, cls_loss (avg) = 0.396299, lr = 0.010000 | |
| iter = 961, accuracy (cur) = 0.720000 (all), 0.645161 (pos), 0.842105 (neg) | |
| iter = 961, accuracy (avg) = 0.818382 (all), 0.809333 (pos), 0.828432 (neg) | |
| data reader: epoch = 0, batch = 962 / 4040 | |
| iter = 962, cls_loss (cur) = 0.348360, cls_loss (avg) = 0.395820, lr = 0.010000 | |
| iter = 962, accuracy (cur) = 0.840000 (all), 0.896552 (pos), 0.761905 (neg) | |
| iter = 962, accuracy (avg) = 0.818598 (all), 0.810205 (pos), 0.827766 (neg) | |
| data reader: epoch = 0, batch = 963 / 4040 | |
| iter = 963, cls_loss (cur) = 0.495301, cls_loss (avg) = 0.396814, lr = 0.010000 | |
| iter = 963, accuracy (cur) = 0.780000 (all), 0.761905 (pos), 0.793103 (neg) | |
| iter = 963, accuracy (avg) = 0.818212 (all), 0.809722 (pos), 0.827420 (neg) | |
| data reader: epoch = 0, batch = 964 / 4040 | |
| iter = 964, cls_loss (cur) = 0.390337, cls_loss (avg) = 0.396750, lr = 0.010000 | |
| iter = 964, accuracy (cur) = 0.800000 (all), 0.888889 (pos), 0.695652 (neg) | |
| iter = 964, accuracy (avg) = 0.818030 (all), 0.810514 (pos), 0.826102 (neg) | |
| data reader: epoch = 0, batch = 965 / 4040 | |
| iter = 965, cls_loss (cur) = 0.490275, cls_loss (avg) = 0.397685, lr = 0.010000 | |
| iter = 965, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 965, accuracy (avg) = 0.817450 (all), 0.809446 (pos), 0.826102 (neg) | |
| data reader: epoch = 0, batch = 966 / 4040 | |
| iter = 966, cls_loss (cur) = 0.409598, cls_loss (avg) = 0.397804, lr = 0.010000 | |
| iter = 966, accuracy (cur) = 0.780000 (all), 0.900000 (pos), 0.700000 (neg) | |
| iter = 966, accuracy (avg) = 0.817075 (all), 0.810351 (pos), 0.824841 (neg) | |
| data reader: epoch = 0, batch = 967 / 4040 | |
| iter = 967, cls_loss (cur) = 0.482556, cls_loss (avg) = 0.398651, lr = 0.010000 | |
| iter = 967, accuracy (cur) = 0.780000 (all), 0.863636 (pos), 0.714286 (neg) | |
| iter = 967, accuracy (avg) = 0.816705 (all), 0.810884 (pos), 0.823735 (neg) | |
| data reader: epoch = 0, batch = 968 / 4040 | |
| iter = 968, cls_loss (cur) = 0.455640, cls_loss (avg) = 0.399221, lr = 0.010000 | |
| iter = 968, accuracy (cur) = 0.760000 (all), 0.714286 (pos), 0.818182 (neg) | |
| iter = 968, accuracy (avg) = 0.816138 (all), 0.809918 (pos), 0.823680 (neg) | |
| data reader: epoch = 0, batch = 969 / 4040 | |
| iter = 969, cls_loss (cur) = 0.397194, cls_loss (avg) = 0.399201, lr = 0.010000 | |
| iter = 969, accuracy (cur) = 0.780000 (all), 0.846154 (pos), 0.708333 (neg) | |
| iter = 969, accuracy (avg) = 0.815776 (all), 0.810281 (pos), 0.822526 (neg) | |
| data reader: epoch = 0, batch = 970 / 4040 | |
| iter = 970, cls_loss (cur) = 0.387689, cls_loss (avg) = 0.399086, lr = 0.010000 | |
| iter = 970, accuracy (cur) = 0.820000 (all), 0.826087 (pos), 0.814815 (neg) | |
| iter = 970, accuracy (avg) = 0.815818 (all), 0.810439 (pos), 0.822449 (neg) | |
| data reader: epoch = 0, batch = 971 / 4040 | |
| iter = 971, cls_loss (cur) = 0.397686, cls_loss (avg) = 0.399072, lr = 0.010000 | |
| iter = 971, accuracy (cur) = 0.800000 (all), 0.772727 (pos), 0.821429 (neg) | |
| iter = 971, accuracy (avg) = 0.815660 (all), 0.810062 (pos), 0.822439 (neg) | |
| data reader: epoch = 0, batch = 972 / 4040 | |
| iter = 972, cls_loss (cur) = 0.376083, cls_loss (avg) = 0.398842, lr = 0.010000 | |
| iter = 972, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 972, accuracy (avg) = 0.815904 (all), 0.810361 (pos), 0.822615 (neg) | |
| data reader: epoch = 0, batch = 973 / 4040 | |
| iter = 973, cls_loss (cur) = 0.416315, cls_loss (avg) = 0.399017, lr = 0.010000 | |
| iter = 973, accuracy (cur) = 0.840000 (all), 0.896552 (pos), 0.761905 (neg) | |
| iter = 973, accuracy (avg) = 0.816145 (all), 0.811223 (pos), 0.822008 (neg) | |
| data reader: epoch = 0, batch = 974 / 4040 | |
| iter = 974, cls_loss (cur) = 0.309455, cls_loss (avg) = 0.398121, lr = 0.010000 | |
| iter = 974, accuracy (cur) = 0.900000 (all), 0.928571 (pos), 0.863636 (neg) | |
| iter = 974, accuracy (avg) = 0.816983 (all), 0.812396 (pos), 0.822424 (neg) | |
| data reader: epoch = 0, batch = 975 / 4040 | |
| iter = 975, cls_loss (cur) = 0.491232, cls_loss (avg) = 0.399052, lr = 0.010000 | |
| iter = 975, accuracy (cur) = 0.760000 (all), 0.650000 (pos), 0.833333 (neg) | |
| iter = 975, accuracy (avg) = 0.816413 (all), 0.810772 (pos), 0.822533 (neg) | |
| data reader: epoch = 0, batch = 976 / 4040 | |
| iter = 976, cls_loss (cur) = 0.500392, cls_loss (avg) = 0.400066, lr = 0.010000 | |
| iter = 976, accuracy (cur) = 0.760000 (all), 0.821429 (pos), 0.681818 (neg) | |
| iter = 976, accuracy (avg) = 0.815849 (all), 0.810879 (pos), 0.821126 (neg) | |
| data reader: epoch = 0, batch = 977 / 4040 | |
| iter = 977, cls_loss (cur) = 0.344327, cls_loss (avg) = 0.399508, lr = 0.010000 | |
| iter = 977, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 977, accuracy (avg) = 0.816491 (all), 0.811699 (pos), 0.821551 (neg) | |
| data reader: epoch = 0, batch = 978 / 4040 | |
| iter = 978, cls_loss (cur) = 0.331063, cls_loss (avg) = 0.398824, lr = 0.010000 | |
| iter = 978, accuracy (cur) = 0.840000 (all), 0.695652 (pos), 0.962963 (neg) | |
| iter = 978, accuracy (avg) = 0.816726 (all), 0.810538 (pos), 0.822965 (neg) | |
| data reader: epoch = 0, batch = 979 / 4040 | |
| iter = 979, cls_loss (cur) = 0.396514, cls_loss (avg) = 0.398801, lr = 0.010000 | |
| iter = 979, accuracy (cur) = 0.820000 (all), 0.793103 (pos), 0.857143 (neg) | |
| iter = 979, accuracy (avg) = 0.816759 (all), 0.810364 (pos), 0.823307 (neg) | |
| data reader: epoch = 0, batch = 980 / 4040 | |
| iter = 980, cls_loss (cur) = 0.333476, cls_loss (avg) = 0.398148, lr = 0.010000 | |
| iter = 980, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 980, accuracy (avg) = 0.817191 (all), 0.811149 (pos), 0.823335 (neg) | |
| data reader: epoch = 0, batch = 981 / 4040 | |
| iter = 981, cls_loss (cur) = 0.454918, cls_loss (avg) = 0.398715, lr = 0.010000 | |
| iter = 981, accuracy (cur) = 0.780000 (all), 0.761905 (pos), 0.793103 (neg) | |
| iter = 981, accuracy (avg) = 0.816819 (all), 0.810657 (pos), 0.823032 (neg) | |
| data reader: epoch = 0, batch = 982 / 4040 | |
| iter = 982, cls_loss (cur) = 0.482096, cls_loss (avg) = 0.399549, lr = 0.010000 | |
| iter = 982, accuracy (cur) = 0.780000 (all), 0.708333 (pos), 0.846154 (neg) | |
| iter = 982, accuracy (avg) = 0.816451 (all), 0.809633 (pos), 0.823264 (neg) | |
| data reader: epoch = 0, batch = 983 / 4040 | |
| iter = 983, cls_loss (cur) = 0.471534, cls_loss (avg) = 0.400269, lr = 0.010000 | |
| iter = 983, accuracy (cur) = 0.760000 (all), 0.750000 (pos), 0.769231 (neg) | |
| iter = 983, accuracy (avg) = 0.815886 (all), 0.809037 (pos), 0.822723 (neg) | |
| data reader: epoch = 0, batch = 984 / 4040 | |
| iter = 984, cls_loss (cur) = 0.459431, cls_loss (avg) = 0.400860, lr = 0.010000 | |
| iter = 984, accuracy (cur) = 0.760000 (all), 0.741935 (pos), 0.789474 (neg) | |
| iter = 984, accuracy (avg) = 0.815327 (all), 0.808366 (pos), 0.822391 (neg) | |
| data reader: epoch = 0, batch = 985 / 4040 | |
| iter = 985, cls_loss (cur) = 0.337574, cls_loss (avg) = 0.400228, lr = 0.010000 | |
| iter = 985, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.852941 (neg) | |
| iter = 985, accuracy (avg) = 0.815774 (all), 0.809032 (pos), 0.822696 (neg) | |
| data reader: epoch = 0, batch = 986 / 4040 | |
| iter = 986, cls_loss (cur) = 0.420790, cls_loss (avg) = 0.400433, lr = 0.010000 | |
| iter = 986, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 986, accuracy (avg) = 0.815416 (all), 0.808250 (pos), 0.822803 (neg) | |
| data reader: epoch = 0, batch = 987 / 4040 | |
| iter = 987, cls_loss (cur) = 0.361486, cls_loss (avg) = 0.400044, lr = 0.010000 | |
| iter = 987, accuracy (cur) = 0.880000 (all), 0.958333 (pos), 0.807692 (neg) | |
| iter = 987, accuracy (avg) = 0.816062 (all), 0.809751 (pos), 0.822651 (neg) | |
| data reader: epoch = 0, batch = 988 / 4040 | |
| iter = 988, cls_loss (cur) = 0.379445, cls_loss (avg) = 0.399838, lr = 0.010000 | |
| iter = 988, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 988, accuracy (avg) = 0.815902 (all), 0.810053 (pos), 0.822025 (neg) | |
| data reader: epoch = 0, batch = 989 / 4040 | |
| iter = 989, cls_loss (cur) = 0.469465, cls_loss (avg) = 0.400534, lr = 0.010000 | |
| iter = 989, accuracy (cur) = 0.780000 (all), 0.782609 (pos), 0.777778 (neg) | |
| iter = 989, accuracy (avg) = 0.815543 (all), 0.809779 (pos), 0.821582 (neg) | |
| data reader: epoch = 0, batch = 990 / 4040 | |
| iter = 990, cls_loss (cur) = 0.314054, cls_loss (avg) = 0.399669, lr = 0.010000 | |
| iter = 990, accuracy (cur) = 0.880000 (all), 0.791667 (pos), 0.961538 (neg) | |
| iter = 990, accuracy (avg) = 0.816187 (all), 0.809598 (pos), 0.822982 (neg) | |
| data reader: epoch = 0, batch = 991 / 4040 | |
| iter = 991, cls_loss (cur) = 0.478623, cls_loss (avg) = 0.400459, lr = 0.010000 | |
| iter = 991, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.807692 (neg) | |
| iter = 991, accuracy (avg) = 0.815425 (all), 0.808168 (pos), 0.822829 (neg) | |
| data reader: epoch = 0, batch = 992 / 4040 | |
| iter = 992, cls_loss (cur) = 0.350609, cls_loss (avg) = 0.399960, lr = 0.010000 | |
| iter = 992, accuracy (cur) = 0.820000 (all), 0.807692 (pos), 0.833333 (neg) | |
| iter = 992, accuracy (avg) = 0.815471 (all), 0.808164 (pos), 0.822934 (neg) | |
| data reader: epoch = 0, batch = 993 / 4040 | |
| iter = 993, cls_loss (cur) = 0.337409, cls_loss (avg) = 0.399335, lr = 0.010000 | |
| iter = 993, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 993, accuracy (avg) = 0.816316 (all), 0.809313 (pos), 0.823455 (neg) | |
| data reader: epoch = 0, batch = 994 / 4040 | |
| iter = 994, cls_loss (cur) = 0.471860, cls_loss (avg) = 0.400060, lr = 0.010000 | |
| iter = 994, accuracy (cur) = 0.800000 (all), 0.720000 (pos), 0.880000 (neg) | |
| iter = 994, accuracy (avg) = 0.816153 (all), 0.808420 (pos), 0.824020 (neg) | |
| data reader: epoch = 0, batch = 995 / 4040 | |
| iter = 995, cls_loss (cur) = 0.459150, cls_loss (avg) = 0.400651, lr = 0.010000 | |
| iter = 995, accuracy (cur) = 0.740000 (all), 0.772727 (pos), 0.714286 (neg) | |
| iter = 995, accuracy (avg) = 0.815392 (all), 0.808063 (pos), 0.822923 (neg) | |
| data reader: epoch = 0, batch = 996 / 4040 | |
| iter = 996, cls_loss (cur) = 0.433077, cls_loss (avg) = 0.400975, lr = 0.010000 | |
| iter = 996, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 996, accuracy (avg) = 0.815438 (all), 0.808196 (pos), 0.822876 (neg) | |
| data reader: epoch = 0, batch = 997 / 4040 | |
| iter = 997, cls_loss (cur) = 0.300164, cls_loss (avg) = 0.399967, lr = 0.010000 | |
| iter = 997, accuracy (cur) = 0.880000 (all), 0.809524 (pos), 0.931034 (neg) | |
| iter = 997, accuracy (avg) = 0.816083 (all), 0.808210 (pos), 0.823957 (neg) | |
| data reader: epoch = 0, batch = 998 / 4040 | |
| iter = 998, cls_loss (cur) = 0.331109, cls_loss (avg) = 0.399279, lr = 0.010000 | |
| iter = 998, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 998, accuracy (avg) = 0.816923 (all), 0.809218 (pos), 0.824646 (neg) | |
| data reader: epoch = 0, batch = 999 / 4040 | |
| iter = 999, cls_loss (cur) = 0.397014, cls_loss (avg) = 0.399256, lr = 0.010000 | |
| iter = 999, accuracy (cur) = 0.820000 (all), 0.962963 (pos), 0.652174 (neg) | |
| iter = 999, accuracy (avg) = 0.816953 (all), 0.810756 (pos), 0.822921 (neg) | |
| data reader: epoch = 0, batch = 1000 / 4040 | |
| iter = 1000, cls_loss (cur) = 0.351667, cls_loss (avg) = 0.398780, lr = 0.010000 | |
| iter = 1000, accuracy (cur) = 0.780000 (all), 0.720000 (pos), 0.840000 (neg) | |
| iter = 1000, accuracy (avg) = 0.816584 (all), 0.809848 (pos), 0.823092 (neg) | |
| data reader: epoch = 0, batch = 1001 / 4040 | |
| iter = 1001, cls_loss (cur) = 0.423069, cls_loss (avg) = 0.399023, lr = 0.010000 | |
| iter = 1001, accuracy (cur) = 0.800000 (all), 0.791667 (pos), 0.807692 (neg) | |
| iter = 1001, accuracy (avg) = 0.816418 (all), 0.809666 (pos), 0.822938 (neg) | |
| data reader: epoch = 0, batch = 1002 / 4040 | |
| iter = 1002, cls_loss (cur) = 0.326699, cls_loss (avg) = 0.398300, lr = 0.010000 | |
| iter = 1002, accuracy (cur) = 0.840000 (all), 0.888889 (pos), 0.782609 (neg) | |
| iter = 1002, accuracy (avg) = 0.816654 (all), 0.810459 (pos), 0.822535 (neg) | |
| data reader: epoch = 0, batch = 1003 / 4040 | |
| iter = 1003, cls_loss (cur) = 0.517119, cls_loss (avg) = 0.399488, lr = 0.010000 | |
| iter = 1003, accuracy (cur) = 0.760000 (all), 0.739130 (pos), 0.777778 (neg) | |
| iter = 1003, accuracy (avg) = 0.816087 (all), 0.809745 (pos), 0.822087 (neg) | |
| data reader: epoch = 0, batch = 1004 / 4040 | |
| iter = 1004, cls_loss (cur) = 0.522899, cls_loss (avg) = 0.400722, lr = 0.010000 | |
| iter = 1004, accuracy (cur) = 0.720000 (all), 0.666667 (pos), 0.769231 (neg) | |
| iter = 1004, accuracy (avg) = 0.815126 (all), 0.808315 (pos), 0.821559 (neg) | |
| data reader: epoch = 0, batch = 1005 / 4040 | |
| iter = 1005, cls_loss (cur) = 0.364137, cls_loss (avg) = 0.400356, lr = 0.010000 | |
| iter = 1005, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 1005, accuracy (avg) = 0.815375 (all), 0.809078 (pos), 0.821260 (neg) | |
| data reader: epoch = 0, batch = 1006 / 4040 | |
| iter = 1006, cls_loss (cur) = 0.360049, cls_loss (avg) = 0.399953, lr = 0.010000 | |
| iter = 1006, accuracy (cur) = 0.860000 (all), 0.884615 (pos), 0.833333 (neg) | |
| iter = 1006, accuracy (avg) = 0.815821 (all), 0.809833 (pos), 0.821381 (neg) | |
| data reader: epoch = 0, batch = 1007 / 4040 | |
| iter = 1007, cls_loss (cur) = 0.406940, cls_loss (avg) = 0.400023, lr = 0.010000 | |
| iter = 1007, accuracy (cur) = 0.840000 (all), 0.806452 (pos), 0.894737 (neg) | |
| iter = 1007, accuracy (avg) = 0.816063 (all), 0.809799 (pos), 0.822114 (neg) | |
| data reader: epoch = 0, batch = 1008 / 4040 | |
| iter = 1008, cls_loss (cur) = 0.411506, cls_loss (avg) = 0.400138, lr = 0.010000 | |
| iter = 1008, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 1008, accuracy (avg) = 0.816303 (all), 0.809632 (pos), 0.822941 (neg) | |
| data reader: epoch = 0, batch = 1009 / 4040 | |
| iter = 1009, cls_loss (cur) = 0.362574, cls_loss (avg) = 0.399762, lr = 0.010000 | |
| iter = 1009, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.900000 (neg) | |
| iter = 1009, accuracy (avg) = 0.816539 (all), 0.809036 (pos), 0.823711 (neg) | |
| data reader: epoch = 0, batch = 1010 / 4040 | |
| iter = 1010, cls_loss (cur) = 0.411705, cls_loss (avg) = 0.399882, lr = 0.010000 | |
| iter = 1010, accuracy (cur) = 0.800000 (all), 0.913043 (pos), 0.703704 (neg) | |
| iter = 1010, accuracy (avg) = 0.816374 (all), 0.810076 (pos), 0.822511 (neg) | |
| data reader: epoch = 0, batch = 1011 / 4040 | |
| iter = 1011, cls_loss (cur) = 0.367065, cls_loss (avg) = 0.399553, lr = 0.010000 | |
| iter = 1011, accuracy (cur) = 0.860000 (all), 0.896552 (pos), 0.809524 (neg) | |
| iter = 1011, accuracy (avg) = 0.816810 (all), 0.810941 (pos), 0.822381 (neg) | |
| data reader: epoch = 0, batch = 1012 / 4040 | |
| iter = 1012, cls_loss (cur) = 0.350175, cls_loss (avg) = 0.399060, lr = 0.010000 | |
| iter = 1012, accuracy (cur) = 0.860000 (all), 0.954545 (pos), 0.785714 (neg) | |
| iter = 1012, accuracy (avg) = 0.817242 (all), 0.812377 (pos), 0.822015 (neg) | |
| data reader: epoch = 0, batch = 1013 / 4040 | |
| iter = 1013, cls_loss (cur) = 0.369798, cls_loss (avg) = 0.398767, lr = 0.010000 | |
| iter = 1013, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 1013, accuracy (avg) = 0.817470 (all), 0.812253 (pos), 0.822594 (neg) | |
| data reader: epoch = 0, batch = 1014 / 4040 | |
| iter = 1014, cls_loss (cur) = 0.367546, cls_loss (avg) = 0.398455, lr = 0.010000 | |
| iter = 1014, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.769231 (neg) | |
| iter = 1014, accuracy (avg) = 0.817295 (all), 0.812464 (pos), 0.822061 (neg) | |
| data reader: epoch = 0, batch = 1015 / 4040 | |
| iter = 1015, cls_loss (cur) = 0.383433, cls_loss (avg) = 0.398305, lr = 0.010000 | |
| iter = 1015, accuracy (cur) = 0.900000 (all), 0.966667 (pos), 0.800000 (neg) | |
| iter = 1015, accuracy (avg) = 0.818122 (all), 0.814006 (pos), 0.821840 (neg) | |
| data reader: epoch = 0, batch = 1016 / 4040 | |
| iter = 1016, cls_loss (cur) = 0.351815, cls_loss (avg) = 0.397840, lr = 0.010000 | |
| iter = 1016, accuracy (cur) = 0.800000 (all), 0.863636 (pos), 0.750000 (neg) | |
| iter = 1016, accuracy (avg) = 0.817941 (all), 0.814502 (pos), 0.821122 (neg) | |
| data reader: epoch = 0, batch = 1017 / 4040 | |
| iter = 1017, cls_loss (cur) = 0.432178, cls_loss (avg) = 0.398183, lr = 0.010000 | |
| iter = 1017, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.771429 (neg) | |
| iter = 1017, accuracy (avg) = 0.817562 (all), 0.814357 (pos), 0.820625 (neg) | |
| data reader: epoch = 0, batch = 1018 / 4040 | |
| iter = 1018, cls_loss (cur) = 0.333058, cls_loss (avg) = 0.397532, lr = 0.010000 | |
| iter = 1018, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.950000 (neg) | |
| iter = 1018, accuracy (avg) = 0.818186 (all), 0.814547 (pos), 0.821919 (neg) | |
| data reader: epoch = 0, batch = 1019 / 4040 | |
| iter = 1019, cls_loss (cur) = 0.437166, cls_loss (avg) = 0.397928, lr = 0.010000 | |
| iter = 1019, accuracy (cur) = 0.780000 (all), 0.652174 (pos), 0.888889 (neg) | |
| iter = 1019, accuracy (avg) = 0.817804 (all), 0.812923 (pos), 0.822588 (neg) | |
| data reader: epoch = 0, batch = 1020 / 4040 | |
| iter = 1020, cls_loss (cur) = 0.361865, cls_loss (avg) = 0.397567, lr = 0.010000 | |
| iter = 1020, accuracy (cur) = 0.820000 (all), 0.689655 (pos), 1.000000 (neg) | |
| iter = 1020, accuracy (avg) = 0.817826 (all), 0.811690 (pos), 0.824362 (neg) | |
| data reader: epoch = 0, batch = 1021 / 4040 | |
| iter = 1021, cls_loss (cur) = 0.389464, cls_loss (avg) = 0.397486, lr = 0.010000 | |
| iter = 1021, accuracy (cur) = 0.780000 (all), 0.758621 (pos), 0.809524 (neg) | |
| iter = 1021, accuracy (avg) = 0.817448 (all), 0.811160 (pos), 0.824214 (neg) | |
| data reader: epoch = 0, batch = 1022 / 4040 | |
| iter = 1022, cls_loss (cur) = 0.483777, cls_loss (avg) = 0.398349, lr = 0.010000 | |
| iter = 1022, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 1022, accuracy (avg) = 0.817273 (all), 0.811048 (pos), 0.823972 (neg) | |
| data reader: epoch = 0, batch = 1023 / 4040 | |
| iter = 1023, cls_loss (cur) = 0.383854, cls_loss (avg) = 0.398204, lr = 0.010000 | |
| iter = 1023, accuracy (cur) = 0.820000 (all), 0.758621 (pos), 0.904762 (neg) | |
| iter = 1023, accuracy (avg) = 0.817301 (all), 0.810524 (pos), 0.824780 (neg) | |
| data reader: epoch = 0, batch = 1024 / 4040 | |
| iter = 1024, cls_loss (cur) = 0.420372, cls_loss (avg) = 0.398426, lr = 0.010000 | |
| iter = 1024, accuracy (cur) = 0.800000 (all), 0.821429 (pos), 0.772727 (neg) | |
| iter = 1024, accuracy (avg) = 0.817128 (all), 0.810633 (pos), 0.824259 (neg) | |
| data reader: epoch = 0, batch = 1025 / 4040 | |
| iter = 1025, cls_loss (cur) = 0.450764, cls_loss (avg) = 0.398949, lr = 0.010000 | |
| iter = 1025, accuracy (cur) = 0.780000 (all), 0.681818 (pos), 0.857143 (neg) | |
| iter = 1025, accuracy (avg) = 0.816756 (all), 0.809345 (pos), 0.824588 (neg) | |
| data reader: epoch = 0, batch = 1026 / 4040 | |
| iter = 1026, cls_loss (cur) = 0.418511, cls_loss (avg) = 0.399145, lr = 0.010000 | |
| iter = 1026, accuracy (cur) = 0.920000 (all), 0.960000 (pos), 0.880000 (neg) | |
| iter = 1026, accuracy (avg) = 0.817789 (all), 0.810851 (pos), 0.825142 (neg) | |
| data reader: epoch = 0, batch = 1027 / 4040 | |
| iter = 1027, cls_loss (cur) = 0.481507, cls_loss (avg) = 0.399969, lr = 0.010000 | |
| iter = 1027, accuracy (cur) = 0.800000 (all), 0.720000 (pos), 0.880000 (neg) | |
| iter = 1027, accuracy (avg) = 0.817611 (all), 0.809943 (pos), 0.825691 (neg) | |
| data reader: epoch = 0, batch = 1028 / 4040 | |
| iter = 1028, cls_loss (cur) = 0.381962, cls_loss (avg) = 0.399789, lr = 0.010000 | |
| iter = 1028, accuracy (cur) = 0.820000 (all), 0.814815 (pos), 0.826087 (neg) | |
| iter = 1028, accuracy (avg) = 0.817635 (all), 0.809992 (pos), 0.825695 (neg) | |
| data reader: epoch = 0, batch = 1029 / 4040 | |
| iter = 1029, cls_loss (cur) = 0.473778, cls_loss (avg) = 0.400529, lr = 0.010000 | |
| iter = 1029, accuracy (cur) = 0.760000 (all), 0.772727 (pos), 0.750000 (neg) | |
| iter = 1029, accuracy (avg) = 0.817058 (all), 0.809619 (pos), 0.824938 (neg) | |
| data reader: epoch = 0, batch = 1030 / 4040 | |
| iter = 1030, cls_loss (cur) = 0.448565, cls_loss (avg) = 0.401009, lr = 0.010000 | |
| iter = 1030, accuracy (cur) = 0.720000 (all), 0.720000 (pos), 0.720000 (neg) | |
| iter = 1030, accuracy (avg) = 0.816088 (all), 0.808723 (pos), 0.823888 (neg) | |
| data reader: epoch = 0, batch = 1031 / 4040 | |
| iter = 1031, cls_loss (cur) = 0.403889, cls_loss (avg) = 0.401038, lr = 0.010000 | |
| iter = 1031, accuracy (cur) = 0.760000 (all), 0.920000 (pos), 0.600000 (neg) | |
| iter = 1031, accuracy (avg) = 0.815527 (all), 0.809835 (pos), 0.821650 (neg) | |
| data reader: epoch = 0, batch = 1032 / 4040 | |
| iter = 1032, cls_loss (cur) = 0.445481, cls_loss (avg) = 0.401482, lr = 0.010000 | |
| iter = 1032, accuracy (cur) = 0.840000 (all), 0.925926 (pos), 0.739130 (neg) | |
| iter = 1032, accuracy (avg) = 0.815772 (all), 0.810996 (pos), 0.820824 (neg) | |
| data reader: epoch = 0, batch = 1033 / 4040 | |
| iter = 1033, cls_loss (cur) = 0.333954, cls_loss (avg) = 0.400807, lr = 0.010000 | |
| iter = 1033, accuracy (cur) = 0.900000 (all), 0.880000 (pos), 0.920000 (neg) | |
| iter = 1033, accuracy (avg) = 0.816614 (all), 0.811686 (pos), 0.821816 (neg) | |
| data reader: epoch = 0, batch = 1034 / 4040 | |
| iter = 1034, cls_loss (cur) = 0.408488, cls_loss (avg) = 0.400884, lr = 0.010000 | |
| iter = 1034, accuracy (cur) = 0.760000 (all), 0.703704 (pos), 0.826087 (neg) | |
| iter = 1034, accuracy (avg) = 0.816048 (all), 0.810607 (pos), 0.821859 (neg) | |
| data reader: epoch = 0, batch = 1035 / 4040 | |
| iter = 1035, cls_loss (cur) = 0.448568, cls_loss (avg) = 0.401360, lr = 0.010000 | |
| iter = 1035, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.769231 (neg) | |
| iter = 1035, accuracy (avg) = 0.815887 (all), 0.810834 (pos), 0.821333 (neg) | |
| data reader: epoch = 0, batch = 1036 / 4040 | |
| iter = 1036, cls_loss (cur) = 0.398332, cls_loss (avg) = 0.401330, lr = 0.010000 | |
| iter = 1036, accuracy (cur) = 0.820000 (all), 0.806452 (pos), 0.842105 (neg) | |
| iter = 1036, accuracy (avg) = 0.815928 (all), 0.810790 (pos), 0.821540 (neg) | |
| data reader: epoch = 0, batch = 1037 / 4040 | |
| iter = 1037, cls_loss (cur) = 0.409920, cls_loss (avg) = 0.401416, lr = 0.010000 | |
| iter = 1037, accuracy (cur) = 0.760000 (all), 0.700000 (pos), 0.800000 (neg) | |
| iter = 1037, accuracy (avg) = 0.815369 (all), 0.809682 (pos), 0.821325 (neg) | |
| data reader: epoch = 0, batch = 1038 / 4040 | |
| iter = 1038, cls_loss (cur) = 0.409275, cls_loss (avg) = 0.401495, lr = 0.010000 | |
| iter = 1038, accuracy (cur) = 0.760000 (all), 0.681818 (pos), 0.821429 (neg) | |
| iter = 1038, accuracy (avg) = 0.814815 (all), 0.808404 (pos), 0.821326 (neg) | |
| data reader: epoch = 0, batch = 1039 / 4040 | |
| iter = 1039, cls_loss (cur) = 0.436916, cls_loss (avg) = 0.401849, lr = 0.010000 | |
| iter = 1039, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.866667 (neg) | |
| iter = 1039, accuracy (avg) = 0.814867 (all), 0.807819 (pos), 0.821779 (neg) | |
| data reader: epoch = 0, batch = 1040 / 4040 | |
| iter = 1040, cls_loss (cur) = 0.472098, cls_loss (avg) = 0.402551, lr = 0.010000 | |
| iter = 1040, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 1040, accuracy (avg) = 0.814319 (all), 0.806141 (pos), 0.822362 (neg) | |
| data reader: epoch = 0, batch = 1041 / 4040 | |
| iter = 1041, cls_loss (cur) = 0.283204, cls_loss (avg) = 0.401358, lr = 0.010000 | |
| iter = 1041, accuracy (cur) = 0.900000 (all), 0.906250 (pos), 0.888889 (neg) | |
| iter = 1041, accuracy (avg) = 0.815175 (all), 0.807142 (pos), 0.823027 (neg) | |
| data reader: epoch = 0, batch = 1042 / 4040 | |
| iter = 1042, cls_loss (cur) = 0.428218, cls_loss (avg) = 0.401627, lr = 0.010000 | |
| iter = 1042, accuracy (cur) = 0.740000 (all), 0.760000 (pos), 0.720000 (neg) | |
| iter = 1042, accuracy (avg) = 0.814424 (all), 0.806671 (pos), 0.821997 (neg) | |
| data reader: epoch = 0, batch = 1043 / 4040 | |
| iter = 1043, cls_loss (cur) = 0.392079, cls_loss (avg) = 0.401531, lr = 0.010000 | |
| iter = 1043, accuracy (cur) = 0.820000 (all), 0.928571 (pos), 0.681818 (neg) | |
| iter = 1043, accuracy (avg) = 0.814479 (all), 0.807890 (pos), 0.820595 (neg) | |
| data reader: epoch = 0, batch = 1044 / 4040 | |
| iter = 1044, cls_loss (cur) = 0.384833, cls_loss (avg) = 0.401364, lr = 0.010000 | |
| iter = 1044, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1044, accuracy (avg) = 0.814935 (all), 0.808740 (pos), 0.820571 (neg) | |
| data reader: epoch = 0, batch = 1045 / 4040 | |
| iter = 1045, cls_loss (cur) = 0.350258, cls_loss (avg) = 0.400853, lr = 0.010000 | |
| iter = 1045, accuracy (cur) = 0.900000 (all), 0.928571 (pos), 0.863636 (neg) | |
| iter = 1045, accuracy (avg) = 0.815785 (all), 0.809938 (pos), 0.821001 (neg) | |
| data reader: epoch = 0, batch = 1046 / 4040 | |
| iter = 1046, cls_loss (cur) = 0.402020, cls_loss (avg) = 0.400865, lr = 0.010000 | |
| iter = 1046, accuracy (cur) = 0.800000 (all), 0.956522 (pos), 0.666667 (neg) | |
| iter = 1046, accuracy (avg) = 0.815627 (all), 0.811404 (pos), 0.819458 (neg) | |
| data reader: epoch = 0, batch = 1047 / 4040 | |
| iter = 1047, cls_loss (cur) = 0.476681, cls_loss (avg) = 0.401623, lr = 0.010000 | |
| iter = 1047, accuracy (cur) = 0.780000 (all), 0.814815 (pos), 0.739130 (neg) | |
| iter = 1047, accuracy (avg) = 0.815271 (all), 0.811438 (pos), 0.818655 (neg) | |
| data reader: epoch = 0, batch = 1048 / 4040 | |
| iter = 1048, cls_loss (cur) = 0.366285, cls_loss (avg) = 0.401269, lr = 0.010000 | |
| iter = 1048, accuracy (cur) = 0.840000 (all), 0.962963 (pos), 0.695652 (neg) | |
| iter = 1048, accuracy (avg) = 0.815518 (all), 0.812953 (pos), 0.817425 (neg) | |
| data reader: epoch = 0, batch = 1049 / 4040 | |
| iter = 1049, cls_loss (cur) = 0.422920, cls_loss (avg) = 0.401486, lr = 0.010000 | |
| iter = 1049, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.714286 (neg) | |
| iter = 1049, accuracy (avg) = 0.814963 (all), 0.813005 (pos), 0.816393 (neg) | |
| data reader: epoch = 0, batch = 1050 / 4040 | |
| iter = 1050, cls_loss (cur) = 0.449349, cls_loss (avg) = 0.401965, lr = 0.010000 | |
| iter = 1050, accuracy (cur) = 0.800000 (all), 0.880000 (pos), 0.720000 (neg) | |
| iter = 1050, accuracy (avg) = 0.814814 (all), 0.813675 (pos), 0.815429 (neg) | |
| data reader: epoch = 0, batch = 1051 / 4040 | |
| iter = 1051, cls_loss (cur) = 0.389638, cls_loss (avg) = 0.401841, lr = 0.010000 | |
| iter = 1051, accuracy (cur) = 0.780000 (all), 0.814815 (pos), 0.739130 (neg) | |
| iter = 1051, accuracy (avg) = 0.814466 (all), 0.813687 (pos), 0.814666 (neg) | |
| data reader: epoch = 0, batch = 1052 / 4040 | |
| iter = 1052, cls_loss (cur) = 0.355500, cls_loss (avg) = 0.401378, lr = 0.010000 | |
| iter = 1052, accuracy (cur) = 0.860000 (all), 0.826087 (pos), 0.888889 (neg) | |
| iter = 1052, accuracy (avg) = 0.814921 (all), 0.813811 (pos), 0.815409 (neg) | |
| data reader: epoch = 0, batch = 1053 / 4040 | |
| iter = 1053, cls_loss (cur) = 0.268560, cls_loss (avg) = 0.400050, lr = 0.010000 | |
| iter = 1053, accuracy (cur) = 0.900000 (all), 0.931034 (pos), 0.857143 (neg) | |
| iter = 1053, accuracy (avg) = 0.815772 (all), 0.814983 (pos), 0.815826 (neg) | |
| data reader: epoch = 0, batch = 1054 / 4040 | |
| iter = 1054, cls_loss (cur) = 0.354212, cls_loss (avg) = 0.399591, lr = 0.010000 | |
| iter = 1054, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 1054, accuracy (avg) = 0.816014 (all), 0.814928 (pos), 0.816288 (neg) | |
| data reader: epoch = 0, batch = 1055 / 4040 | |
| iter = 1055, cls_loss (cur) = 0.379791, cls_loss (avg) = 0.399393, lr = 0.010000 | |
| iter = 1055, accuracy (cur) = 0.820000 (all), 0.793103 (pos), 0.857143 (neg) | |
| iter = 1055, accuracy (avg) = 0.816054 (all), 0.814710 (pos), 0.816697 (neg) | |
| data reader: epoch = 0, batch = 1056 / 4040 | |
| iter = 1056, cls_loss (cur) = 0.377045, cls_loss (avg) = 0.399170, lr = 0.010000 | |
| iter = 1056, accuracy (cur) = 0.840000 (all), 0.760000 (pos), 0.920000 (neg) | |
| iter = 1056, accuracy (avg) = 0.816293 (all), 0.814163 (pos), 0.817730 (neg) | |
| data reader: epoch = 0, batch = 1057 / 4040 | |
| iter = 1057, cls_loss (cur) = 0.378867, cls_loss (avg) = 0.398967, lr = 0.010000 | |
| iter = 1057, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1057, accuracy (avg) = 0.816730 (all), 0.814821 (pos), 0.817953 (neg) | |
| data reader: epoch = 0, batch = 1058 / 4040 | |
| iter = 1058, cls_loss (cur) = 0.501384, cls_loss (avg) = 0.399991, lr = 0.010000 | |
| iter = 1058, accuracy (cur) = 0.700000 (all), 0.709677 (pos), 0.684211 (neg) | |
| iter = 1058, accuracy (avg) = 0.815563 (all), 0.813770 (pos), 0.816615 (neg) | |
| data reader: epoch = 0, batch = 1059 / 4040 | |
| iter = 1059, cls_loss (cur) = 0.367710, cls_loss (avg) = 0.399668, lr = 0.010000 | |
| iter = 1059, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 1059, accuracy (avg) = 0.815607 (all), 0.813325 (pos), 0.817199 (neg) | |
| data reader: epoch = 0, batch = 1060 / 4040 | |
| iter = 1060, cls_loss (cur) = 0.484036, cls_loss (avg) = 0.400512, lr = 0.010000 | |
| iter = 1060, accuracy (cur) = 0.840000 (all), 0.866667 (pos), 0.800000 (neg) | |
| iter = 1060, accuracy (avg) = 0.815851 (all), 0.813858 (pos), 0.817027 (neg) | |
| data reader: epoch = 0, batch = 1061 / 4040 | |
| iter = 1061, cls_loss (cur) = 0.377077, cls_loss (avg) = 0.400278, lr = 0.010000 | |
| iter = 1061, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1061, accuracy (avg) = 0.816293 (all), 0.814648 (pos), 0.817039 (neg) | |
| data reader: epoch = 0, batch = 1062 / 4040 | |
| iter = 1062, cls_loss (cur) = 0.317403, cls_loss (avg) = 0.399449, lr = 0.010000 | |
| iter = 1062, accuracy (cur) = 0.900000 (all), 0.958333 (pos), 0.846154 (neg) | |
| iter = 1062, accuracy (avg) = 0.817130 (all), 0.816085 (pos), 0.817330 (neg) | |
| data reader: epoch = 0, batch = 1063 / 4040 | |
| iter = 1063, cls_loss (cur) = 0.319518, cls_loss (avg) = 0.398649, lr = 0.010000 | |
| iter = 1063, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.857143 (neg) | |
| iter = 1063, accuracy (avg) = 0.817759 (all), 0.817015 (pos), 0.817728 (neg) | |
| data reader: epoch = 0, batch = 1064 / 4040 | |
| iter = 1064, cls_loss (cur) = 0.410084, cls_loss (avg) = 0.398764, lr = 0.010000 | |
| iter = 1064, accuracy (cur) = 0.760000 (all), 0.846154 (pos), 0.666667 (neg) | |
| iter = 1064, accuracy (avg) = 0.817181 (all), 0.817306 (pos), 0.816217 (neg) | |
| data reader: epoch = 0, batch = 1065 / 4040 | |
| iter = 1065, cls_loss (cur) = 0.342549, cls_loss (avg) = 0.398202, lr = 0.010000 | |
| iter = 1065, accuracy (cur) = 0.880000 (all), 0.965517 (pos), 0.761905 (neg) | |
| iter = 1065, accuracy (avg) = 0.817809 (all), 0.818788 (pos), 0.815674 (neg) | |
| data reader: epoch = 0, batch = 1066 / 4040 | |
| iter = 1066, cls_loss (cur) = 0.448483, cls_loss (avg) = 0.398704, lr = 0.010000 | |
| iter = 1066, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.807692 (neg) | |
| iter = 1066, accuracy (avg) = 0.817031 (all), 0.817267 (pos), 0.815594 (neg) | |
| data reader: epoch = 0, batch = 1067 / 4040 | |
| iter = 1067, cls_loss (cur) = 0.381656, cls_loss (avg) = 0.398534, lr = 0.010000 | |
| iter = 1067, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 1067, accuracy (avg) = 0.817261 (all), 0.817428 (pos), 0.815900 (neg) | |
| data reader: epoch = 0, batch = 1068 / 4040 | |
| iter = 1068, cls_loss (cur) = 0.392453, cls_loss (avg) = 0.398473, lr = 0.010000 | |
| iter = 1068, accuracy (cur) = 0.780000 (all), 0.640000 (pos), 0.920000 (neg) | |
| iter = 1068, accuracy (avg) = 0.816888 (all), 0.815654 (pos), 0.816941 (neg) | |
| data reader: epoch = 0, batch = 1069 / 4040 | |
| iter = 1069, cls_loss (cur) = 0.409215, cls_loss (avg) = 0.398581, lr = 0.010000 | |
| iter = 1069, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 1069, accuracy (avg) = 0.816919 (all), 0.815354 (pos), 0.817408 (neg) | |
| data reader: epoch = 0, batch = 1070 / 4040 | |
| iter = 1070, cls_loss (cur) = 0.394270, cls_loss (avg) = 0.398538, lr = 0.010000 | |
| iter = 1070, accuracy (cur) = 0.760000 (all), 0.842105 (pos), 0.709677 (neg) | |
| iter = 1070, accuracy (avg) = 0.816350 (all), 0.815622 (pos), 0.816331 (neg) | |
| data reader: epoch = 0, batch = 1071 / 4040 | |
| iter = 1071, cls_loss (cur) = 0.317902, cls_loss (avg) = 0.397731, lr = 0.010000 | |
| iter = 1071, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.863636 (neg) | |
| iter = 1071, accuracy (avg) = 0.816787 (all), 0.816037 (pos), 0.816804 (neg) | |
| data reader: epoch = 0, batch = 1072 / 4040 | |
| iter = 1072, cls_loss (cur) = 0.431076, cls_loss (avg) = 0.398065, lr = 0.010000 | |
| iter = 1072, accuracy (cur) = 0.780000 (all), 0.741935 (pos), 0.842105 (neg) | |
| iter = 1072, accuracy (avg) = 0.816419 (all), 0.815296 (pos), 0.817057 (neg) | |
| data reader: epoch = 0, batch = 1073 / 4040 | |
| iter = 1073, cls_loss (cur) = 0.337350, cls_loss (avg) = 0.397457, lr = 0.010000 | |
| iter = 1073, accuracy (cur) = 0.800000 (all), 0.863636 (pos), 0.750000 (neg) | |
| iter = 1073, accuracy (avg) = 0.816255 (all), 0.815779 (pos), 0.816386 (neg) | |
| data reader: epoch = 0, batch = 1074 / 4040 | |
| iter = 1074, cls_loss (cur) = 0.333154, cls_loss (avg) = 0.396814, lr = 0.010000 | |
| iter = 1074, accuracy (cur) = 0.880000 (all), 0.857143 (pos), 0.909091 (neg) | |
| iter = 1074, accuracy (avg) = 0.816892 (all), 0.816193 (pos), 0.817313 (neg) | |
| data reader: epoch = 0, batch = 1075 / 4040 | |
| iter = 1075, cls_loss (cur) = 0.337431, cls_loss (avg) = 0.396221, lr = 0.010000 | |
| iter = 1075, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 1075, accuracy (avg) = 0.817323 (all), 0.817231 (pos), 0.817140 (neg) | |
| data reader: epoch = 0, batch = 1076 / 4040 | |
| iter = 1076, cls_loss (cur) = 0.406792, cls_loss (avg) = 0.396326, lr = 0.010000 | |
| iter = 1076, accuracy (cur) = 0.840000 (all), 0.923077 (pos), 0.750000 (neg) | |
| iter = 1076, accuracy (avg) = 0.817550 (all), 0.818289 (pos), 0.816469 (neg) | |
| data reader: epoch = 0, batch = 1077 / 4040 | |
| iter = 1077, cls_loss (cur) = 0.400365, cls_loss (avg) = 0.396367, lr = 0.010000 | |
| iter = 1077, accuracy (cur) = 0.840000 (all), 0.821429 (pos), 0.863636 (neg) | |
| iter = 1077, accuracy (avg) = 0.817774 (all), 0.818321 (pos), 0.816940 (neg) | |
| data reader: epoch = 0, batch = 1078 / 4040 | |
| iter = 1078, cls_loss (cur) = 0.432211, cls_loss (avg) = 0.396725, lr = 0.010000 | |
| iter = 1078, accuracy (cur) = 0.800000 (all), 0.909091 (pos), 0.714286 (neg) | |
| iter = 1078, accuracy (avg) = 0.817597 (all), 0.819229 (pos), 0.815914 (neg) | |
| data reader: epoch = 0, batch = 1079 / 4040 | |
| iter = 1079, cls_loss (cur) = 0.265813, cls_loss (avg) = 0.395416, lr = 0.010000 | |
| iter = 1079, accuracy (cur) = 0.900000 (all), 0.954545 (pos), 0.857143 (neg) | |
| iter = 1079, accuracy (avg) = 0.818421 (all), 0.820582 (pos), 0.816326 (neg) | |
| data reader: epoch = 0, batch = 1080 / 4040 | |
| iter = 1080, cls_loss (cur) = 0.496972, cls_loss (avg) = 0.396432, lr = 0.010000 | |
| iter = 1080, accuracy (cur) = 0.760000 (all), 0.807692 (pos), 0.708333 (neg) | |
| iter = 1080, accuracy (avg) = 0.817836 (all), 0.820453 (pos), 0.815246 (neg) | |
| data reader: epoch = 0, batch = 1081 / 4040 | |
| iter = 1081, cls_loss (cur) = 0.337426, cls_loss (avg) = 0.395842, lr = 0.010000 | |
| iter = 1081, accuracy (cur) = 0.840000 (all), 0.814815 (pos), 0.869565 (neg) | |
| iter = 1081, accuracy (avg) = 0.818058 (all), 0.820396 (pos), 0.815789 (neg) | |
| data reader: epoch = 0, batch = 1082 / 4040 | |
| iter = 1082, cls_loss (cur) = 0.449381, cls_loss (avg) = 0.396377, lr = 0.010000 | |
| iter = 1082, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.647059 (neg) | |
| iter = 1082, accuracy (avg) = 0.817477 (all), 0.820374 (pos), 0.814102 (neg) | |
| data reader: epoch = 0, batch = 1083 / 4040 | |
| iter = 1083, cls_loss (cur) = 0.498747, cls_loss (avg) = 0.397401, lr = 0.010000 | |
| iter = 1083, accuracy (cur) = 0.780000 (all), 0.947368 (pos), 0.677419 (neg) | |
| iter = 1083, accuracy (avg) = 0.817103 (all), 0.821644 (pos), 0.812735 (neg) | |
| data reader: epoch = 0, batch = 1084 / 4040 | |
| iter = 1084, cls_loss (cur) = 0.381286, cls_loss (avg) = 0.397239, lr = 0.010000 | |
| iter = 1084, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 1084, accuracy (avg) = 0.816932 (all), 0.821828 (pos), 0.812208 (neg) | |
| data reader: epoch = 0, batch = 1085 / 4040 | |
| iter = 1085, cls_loss (cur) = 0.342247, cls_loss (avg) = 0.396690, lr = 0.010000 | |
| iter = 1085, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 1085, accuracy (avg) = 0.817362 (all), 0.822305 (pos), 0.812604 (neg) | |
| data reader: epoch = 0, batch = 1086 / 4040 | |
| iter = 1086, cls_loss (cur) = 0.370216, cls_loss (avg) = 0.396425, lr = 0.010000 | |
| iter = 1086, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 1086, accuracy (avg) = 0.817389 (all), 0.821999 (pos), 0.812940 (neg) | |
| data reader: epoch = 0, batch = 1087 / 4040 | |
| iter = 1087, cls_loss (cur) = 0.390965, cls_loss (avg) = 0.396370, lr = 0.010000 | |
| iter = 1087, accuracy (cur) = 0.800000 (all), 0.739130 (pos), 0.851852 (neg) | |
| iter = 1087, accuracy (avg) = 0.817215 (all), 0.821170 (pos), 0.813329 (neg) | |
| data reader: epoch = 0, batch = 1088 / 4040 | |
| iter = 1088, cls_loss (cur) = 0.298939, cls_loss (avg) = 0.395396, lr = 0.010000 | |
| iter = 1088, accuracy (cur) = 0.860000 (all), 0.818182 (pos), 0.892857 (neg) | |
| iter = 1088, accuracy (avg) = 0.817643 (all), 0.821140 (pos), 0.814124 (neg) | |
| data reader: epoch = 0, batch = 1089 / 4040 | |
| iter = 1089, cls_loss (cur) = 0.432403, cls_loss (avg) = 0.395766, lr = 0.010000 | |
| iter = 1089, accuracy (cur) = 0.740000 (all), 0.727273 (pos), 0.764706 (neg) | |
| iter = 1089, accuracy (avg) = 0.816866 (all), 0.820202 (pos), 0.813630 (neg) | |
| data reader: epoch = 0, batch = 1090 / 4040 | |
| iter = 1090, cls_loss (cur) = 0.388666, cls_loss (avg) = 0.395695, lr = 0.010000 | |
| iter = 1090, accuracy (cur) = 0.780000 (all), 0.724138 (pos), 0.857143 (neg) | |
| iter = 1090, accuracy (avg) = 0.816498 (all), 0.819241 (pos), 0.814065 (neg) | |
| data reader: epoch = 0, batch = 1091 / 4040 | |
| iter = 1091, cls_loss (cur) = 0.294893, cls_loss (avg) = 0.394687, lr = 0.010000 | |
| iter = 1091, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1091, accuracy (avg) = 0.816933 (all), 0.819799 (pos), 0.814386 (neg) | |
| data reader: epoch = 0, batch = 1092 / 4040 | |
| iter = 1092, cls_loss (cur) = 0.416123, cls_loss (avg) = 0.394901, lr = 0.010000 | |
| iter = 1092, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.771429 (neg) | |
| iter = 1092, accuracy (avg) = 0.816563 (all), 0.819601 (pos), 0.813956 (neg) | |
| data reader: epoch = 0, batch = 1093 / 4040 | |
| iter = 1093, cls_loss (cur) = 0.380167, cls_loss (avg) = 0.394754, lr = 0.010000 | |
| iter = 1093, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.818182 (neg) | |
| iter = 1093, accuracy (avg) = 0.816198 (all), 0.818905 (pos), 0.813999 (neg) | |
| data reader: epoch = 0, batch = 1094 / 4040 | |
| iter = 1094, cls_loss (cur) = 0.434276, cls_loss (avg) = 0.395149, lr = 0.010000 | |
| iter = 1094, accuracy (cur) = 0.780000 (all), 0.789474 (pos), 0.774194 (neg) | |
| iter = 1094, accuracy (avg) = 0.815836 (all), 0.818610 (pos), 0.813601 (neg) | |
| data reader: epoch = 0, batch = 1095 / 4040 | |
| iter = 1095, cls_loss (cur) = 0.428088, cls_loss (avg) = 0.395479, lr = 0.010000 | |
| iter = 1095, accuracy (cur) = 0.760000 (all), 0.666667 (pos), 0.869565 (neg) | |
| iter = 1095, accuracy (avg) = 0.815277 (all), 0.817091 (pos), 0.814160 (neg) | |
| data reader: epoch = 0, batch = 1096 / 4040 | |
| iter = 1096, cls_loss (cur) = 0.453159, cls_loss (avg) = 0.396055, lr = 0.010000 | |
| iter = 1096, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.730769 (neg) | |
| iter = 1096, accuracy (avg) = 0.814525 (all), 0.816420 (pos), 0.813326 (neg) | |
| data reader: epoch = 0, batch = 1097 / 4040 | |
| iter = 1097, cls_loss (cur) = 0.399736, cls_loss (avg) = 0.396092, lr = 0.010000 | |
| iter = 1097, accuracy (cur) = 0.860000 (all), 0.904762 (pos), 0.827586 (neg) | |
| iter = 1097, accuracy (avg) = 0.814979 (all), 0.817303 (pos), 0.813469 (neg) | |
| data reader: epoch = 0, batch = 1098 / 4040 | |
| iter = 1098, cls_loss (cur) = 0.480824, cls_loss (avg) = 0.396939, lr = 0.010000 | |
| iter = 1098, accuracy (cur) = 0.740000 (all), 0.720000 (pos), 0.760000 (neg) | |
| iter = 1098, accuracy (avg) = 0.814230 (all), 0.816330 (pos), 0.812934 (neg) | |
| data reader: epoch = 0, batch = 1099 / 4040 | |
| iter = 1099, cls_loss (cur) = 0.447603, cls_loss (avg) = 0.397446, lr = 0.010000 | |
| iter = 1099, accuracy (cur) = 0.780000 (all), 0.740741 (pos), 0.826087 (neg) | |
| iter = 1099, accuracy (avg) = 0.813887 (all), 0.815574 (pos), 0.813066 (neg) | |
| data reader: epoch = 0, batch = 1100 / 4040 | |
| iter = 1100, cls_loss (cur) = 0.342382, cls_loss (avg) = 0.396895, lr = 0.010000 | |
| iter = 1100, accuracy (cur) = 0.860000 (all), 0.821429 (pos), 0.909091 (neg) | |
| iter = 1100, accuracy (avg) = 0.814348 (all), 0.815633 (pos), 0.814026 (neg) | |
| data reader: epoch = 0, batch = 1101 / 4040 | |
| iter = 1101, cls_loss (cur) = 0.360698, cls_loss (avg) = 0.396534, lr = 0.010000 | |
| iter = 1101, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.812500 (neg) | |
| iter = 1101, accuracy (avg) = 0.814405 (all), 0.815810 (pos), 0.814011 (neg) | |
| data reader: epoch = 0, batch = 1102 / 4040 | |
| iter = 1102, cls_loss (cur) = 0.458478, cls_loss (avg) = 0.397153, lr = 0.010000 | |
| iter = 1102, accuracy (cur) = 0.760000 (all), 0.846154 (pos), 0.666667 (neg) | |
| iter = 1102, accuracy (avg) = 0.813861 (all), 0.816113 (pos), 0.812537 (neg) | |
| data reader: epoch = 0, batch = 1103 / 4040 | |
| iter = 1103, cls_loss (cur) = 0.361569, cls_loss (avg) = 0.396797, lr = 0.010000 | |
| iter = 1103, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.884615 (neg) | |
| iter = 1103, accuracy (avg) = 0.813922 (all), 0.815452 (pos), 0.813258 (neg) | |
| data reader: epoch = 0, batch = 1104 / 4040 | |
| iter = 1104, cls_loss (cur) = 0.313315, cls_loss (avg) = 0.395962, lr = 0.010000 | |
| iter = 1104, accuracy (cur) = 0.920000 (all), 0.960000 (pos), 0.880000 (neg) | |
| iter = 1104, accuracy (avg) = 0.814983 (all), 0.816898 (pos), 0.813926 (neg) | |
| data reader: epoch = 0, batch = 1105 / 4040 | |
| iter = 1105, cls_loss (cur) = 0.389808, cls_loss (avg) = 0.395901, lr = 0.010000 | |
| iter = 1105, accuracy (cur) = 0.800000 (all), 0.807692 (pos), 0.791667 (neg) | |
| iter = 1105, accuracy (avg) = 0.814833 (all), 0.816806 (pos), 0.813703 (neg) | |
| data reader: epoch = 0, batch = 1106 / 4040 | |
| iter = 1106, cls_loss (cur) = 0.436134, cls_loss (avg) = 0.396303, lr = 0.010000 | |
| iter = 1106, accuracy (cur) = 0.780000 (all), 0.826087 (pos), 0.740741 (neg) | |
| iter = 1106, accuracy (avg) = 0.814485 (all), 0.816898 (pos), 0.812973 (neg) | |
| data reader: epoch = 0, batch = 1107 / 4040 | |
| iter = 1107, cls_loss (cur) = 0.432391, cls_loss (avg) = 0.396664, lr = 0.010000 | |
| iter = 1107, accuracy (cur) = 0.760000 (all), 0.769231 (pos), 0.750000 (neg) | |
| iter = 1107, accuracy (avg) = 0.813940 (all), 0.816422 (pos), 0.812344 (neg) | |
| data reader: epoch = 0, batch = 1108 / 4040 | |
| iter = 1108, cls_loss (cur) = 0.404885, cls_loss (avg) = 0.396746, lr = 0.010000 | |
| iter = 1108, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 1108, accuracy (avg) = 0.814401 (all), 0.816719 (pos), 0.812970 (neg) | |
| data reader: epoch = 0, batch = 1109 / 4040 | |
| iter = 1109, cls_loss (cur) = 0.374110, cls_loss (avg) = 0.396520, lr = 0.010000 | |
| iter = 1109, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1109, accuracy (avg) = 0.814857 (all), 0.817352 (pos), 0.813240 (neg) | |
| data reader: epoch = 0, batch = 1110 / 4040 | |
| iter = 1110, cls_loss (cur) = 0.300363, cls_loss (avg) = 0.395558, lr = 0.010000 | |
| iter = 1110, accuracy (cur) = 0.880000 (all), 0.842105 (pos), 0.903226 (neg) | |
| iter = 1110, accuracy (avg) = 0.815508 (all), 0.817599 (pos), 0.814140 (neg) | |
| data reader: epoch = 0, batch = 1111 / 4040 | |
| iter = 1111, cls_loss (cur) = 0.301584, cls_loss (avg) = 0.394618, lr = 0.010000 | |
| iter = 1111, accuracy (cur) = 0.900000 (all), 0.892857 (pos), 0.909091 (neg) | |
| iter = 1111, accuracy (avg) = 0.816353 (all), 0.818352 (pos), 0.815090 (neg) | |
| data reader: epoch = 0, batch = 1112 / 4040 | |
| iter = 1112, cls_loss (cur) = 0.384444, cls_loss (avg) = 0.394517, lr = 0.010000 | |
| iter = 1112, accuracy (cur) = 0.820000 (all), 0.787879 (pos), 0.882353 (neg) | |
| iter = 1112, accuracy (avg) = 0.816389 (all), 0.818047 (pos), 0.815762 (neg) | |
| data reader: epoch = 0, batch = 1113 / 4040 | |
| iter = 1113, cls_loss (cur) = 0.376195, cls_loss (avg) = 0.394334, lr = 0.010000 | |
| iter = 1113, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 1113, accuracy (avg) = 0.816626 (all), 0.818328 (pos), 0.815938 (neg) | |
| data reader: epoch = 0, batch = 1114 / 4040 | |
| iter = 1114, cls_loss (cur) = 0.330556, cls_loss (avg) = 0.393696, lr = 0.010000 | |
| iter = 1114, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 1114, accuracy (avg) = 0.816859 (all), 0.818145 (pos), 0.816579 (neg) | |
| data reader: epoch = 0, batch = 1115 / 4040 | |
| iter = 1115, cls_loss (cur) = 0.325065, cls_loss (avg) = 0.393009, lr = 0.010000 | |
| iter = 1115, accuracy (cur) = 0.880000 (all), 0.950000 (pos), 0.833333 (neg) | |
| iter = 1115, accuracy (avg) = 0.817491 (all), 0.819464 (pos), 0.816746 (neg) | |
| data reader: epoch = 0, batch = 1116 / 4040 | |
| iter = 1116, cls_loss (cur) = 0.271485, cls_loss (avg) = 0.391794, lr = 0.010000 | |
| iter = 1116, accuracy (cur) = 0.940000 (all), 0.925926 (pos), 0.956522 (neg) | |
| iter = 1116, accuracy (avg) = 0.818716 (all), 0.820528 (pos), 0.818144 (neg) | |
| data reader: epoch = 0, batch = 1117 / 4040 | |
| iter = 1117, cls_loss (cur) = 0.269520, cls_loss (avg) = 0.390571, lr = 0.010000 | |
| iter = 1117, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.882353 (neg) | |
| iter = 1117, accuracy (avg) = 0.819529 (all), 0.821414 (pos), 0.818786 (neg) | |
| data reader: epoch = 0, batch = 1118 / 4040 | |
| iter = 1118, cls_loss (cur) = 0.280151, cls_loss (avg) = 0.389467, lr = 0.010000 | |
| iter = 1118, accuracy (cur) = 0.900000 (all), 0.958333 (pos), 0.846154 (neg) | |
| iter = 1118, accuracy (avg) = 0.820333 (all), 0.822783 (pos), 0.819060 (neg) | |
| data reader: epoch = 0, batch = 1119 / 4040 | |
| iter = 1119, cls_loss (cur) = 0.358695, cls_loss (avg) = 0.389160, lr = 0.010000 | |
| iter = 1119, accuracy (cur) = 0.820000 (all), 0.875000 (pos), 0.769231 (neg) | |
| iter = 1119, accuracy (avg) = 0.820330 (all), 0.823305 (pos), 0.818562 (neg) | |
| data reader: epoch = 0, batch = 1120 / 4040 | |
| iter = 1120, cls_loss (cur) = 0.284228, cls_loss (avg) = 0.388110, lr = 0.010000 | |
| iter = 1120, accuracy (cur) = 0.900000 (all), 1.000000 (pos), 0.782609 (neg) | |
| iter = 1120, accuracy (avg) = 0.821127 (all), 0.825072 (pos), 0.818202 (neg) | |
| data reader: epoch = 0, batch = 1121 / 4040 | |
| iter = 1121, cls_loss (cur) = 0.302069, cls_loss (avg) = 0.387250, lr = 0.010000 | |
| iter = 1121, accuracy (cur) = 0.860000 (all), 0.838710 (pos), 0.894737 (neg) | |
| iter = 1121, accuracy (avg) = 0.821515 (all), 0.825209 (pos), 0.818967 (neg) | |
| data reader: epoch = 0, batch = 1122 / 4040 | |
| iter = 1122, cls_loss (cur) = 0.276656, cls_loss (avg) = 0.386144, lr = 0.010000 | |
| iter = 1122, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1122, accuracy (avg) = 0.822100 (all), 0.826087 (pos), 0.819296 (neg) | |
| data reader: epoch = 0, batch = 1123 / 4040 | |
| iter = 1123, cls_loss (cur) = 0.342785, cls_loss (avg) = 0.385710, lr = 0.010000 | |
| iter = 1123, accuracy (cur) = 0.880000 (all), 0.875000 (pos), 0.884615 (neg) | |
| iter = 1123, accuracy (avg) = 0.822679 (all), 0.826576 (pos), 0.819949 (neg) | |
| data reader: epoch = 0, batch = 1124 / 4040 | |
| iter = 1124, cls_loss (cur) = 0.416817, cls_loss (avg) = 0.386021, lr = 0.010000 | |
| iter = 1124, accuracy (cur) = 0.760000 (all), 0.833333 (pos), 0.692308 (neg) | |
| iter = 1124, accuracy (avg) = 0.822052 (all), 0.826644 (pos), 0.818673 (neg) | |
| data reader: epoch = 0, batch = 1125 / 4040 | |
| iter = 1125, cls_loss (cur) = 0.381492, cls_loss (avg) = 0.385976, lr = 0.010000 | |
| iter = 1125, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 1125, accuracy (avg) = 0.821832 (all), 0.826777 (pos), 0.818086 (neg) | |
| data reader: epoch = 0, batch = 1126 / 4040 | |
| iter = 1126, cls_loss (cur) = 0.410570, cls_loss (avg) = 0.386222, lr = 0.010000 | |
| iter = 1126, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 1126, accuracy (avg) = 0.822214 (all), 0.826971 (pos), 0.818655 (neg) | |
| data reader: epoch = 0, batch = 1127 / 4040 | |
| iter = 1127, cls_loss (cur) = 0.454031, cls_loss (avg) = 0.386900, lr = 0.010000 | |
| iter = 1127, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.833333 (neg) | |
| iter = 1127, accuracy (avg) = 0.821791 (all), 0.826201 (pos), 0.818802 (neg) | |
| data reader: epoch = 0, batch = 1128 / 4040 | |
| iter = 1128, cls_loss (cur) = 0.315156, cls_loss (avg) = 0.386183, lr = 0.010000 | |
| iter = 1128, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 1128, accuracy (avg) = 0.822574 (all), 0.827030 (pos), 0.819543 (neg) | |
| data reader: epoch = 0, batch = 1129 / 4040 | |
| iter = 1129, cls_loss (cur) = 0.411256, cls_loss (avg) = 0.386433, lr = 0.010000 | |
| iter = 1129, accuracy (cur) = 0.760000 (all), 0.727273 (pos), 0.823529 (neg) | |
| iter = 1129, accuracy (avg) = 0.821948 (all), 0.826033 (pos), 0.819583 (neg) | |
| data reader: epoch = 0, batch = 1130 / 4040 | |
| iter = 1130, cls_loss (cur) = 0.292403, cls_loss (avg) = 0.385493, lr = 0.010000 | |
| iter = 1130, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 1130, accuracy (avg) = 0.822528 (all), 0.826234 (pos), 0.820553 (neg) | |
| data reader: epoch = 0, batch = 1131 / 4040 | |
| iter = 1131, cls_loss (cur) = 0.307173, cls_loss (avg) = 0.384710, lr = 0.010000 | |
| iter = 1131, accuracy (cur) = 0.880000 (all), 0.777778 (pos), 0.937500 (neg) | |
| iter = 1131, accuracy (avg) = 0.823103 (all), 0.825749 (pos), 0.821723 (neg) | |
| data reader: epoch = 0, batch = 1132 / 4040 | |
| iter = 1132, cls_loss (cur) = 0.318682, cls_loss (avg) = 0.384050, lr = 0.010000 | |
| iter = 1132, accuracy (cur) = 0.820000 (all), 0.850000 (pos), 0.800000 (neg) | |
| iter = 1132, accuracy (avg) = 0.823072 (all), 0.825992 (pos), 0.821506 (neg) | |
| data reader: epoch = 0, batch = 1133 / 4040 | |
| iter = 1133, cls_loss (cur) = 0.272315, cls_loss (avg) = 0.382932, lr = 0.010000 | |
| iter = 1133, accuracy (cur) = 0.860000 (all), 0.904762 (pos), 0.827586 (neg) | |
| iter = 1133, accuracy (avg) = 0.823441 (all), 0.826779 (pos), 0.821566 (neg) | |
| data reader: epoch = 0, batch = 1134 / 4040 | |
| iter = 1134, cls_loss (cur) = 0.515656, cls_loss (avg) = 0.384259, lr = 0.010000 | |
| iter = 1134, accuracy (cur) = 0.780000 (all), 0.880000 (pos), 0.680000 (neg) | |
| iter = 1134, accuracy (avg) = 0.823007 (all), 0.827312 (pos), 0.820151 (neg) | |
| data reader: epoch = 0, batch = 1135 / 4040 | |
| iter = 1135, cls_loss (cur) = 0.362798, cls_loss (avg) = 0.384045, lr = 0.010000 | |
| iter = 1135, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 1135, accuracy (avg) = 0.823377 (all), 0.827734 (pos), 0.820468 (neg) | |
| data reader: epoch = 0, batch = 1136 / 4040 | |
| iter = 1136, cls_loss (cur) = 0.510838, cls_loss (avg) = 0.385313, lr = 0.010000 | |
| iter = 1136, accuracy (cur) = 0.720000 (all), 0.600000 (pos), 0.900000 (neg) | |
| iter = 1136, accuracy (avg) = 0.822343 (all), 0.825457 (pos), 0.821263 (neg) | |
| data reader: epoch = 0, batch = 1137 / 4040 | |
| iter = 1137, cls_loss (cur) = 0.301790, cls_loss (avg) = 0.384478, lr = 0.010000 | |
| iter = 1137, accuracy (cur) = 0.940000 (all), 0.913043 (pos), 0.962963 (neg) | |
| iter = 1137, accuracy (avg) = 0.823520 (all), 0.826333 (pos), 0.822680 (neg) | |
| data reader: epoch = 0, batch = 1138 / 4040 | |
| iter = 1138, cls_loss (cur) = 0.430920, cls_loss (avg) = 0.384942, lr = 0.010000 | |
| iter = 1138, accuracy (cur) = 0.720000 (all), 0.821429 (pos), 0.590909 (neg) | |
| iter = 1138, accuracy (avg) = 0.822484 (all), 0.826284 (pos), 0.820362 (neg) | |
| data reader: epoch = 0, batch = 1139 / 4040 | |
| iter = 1139, cls_loss (cur) = 0.319680, cls_loss (avg) = 0.384289, lr = 0.010000 | |
| iter = 1139, accuracy (cur) = 0.860000 (all), 0.904762 (pos), 0.827586 (neg) | |
| iter = 1139, accuracy (avg) = 0.822860 (all), 0.827068 (pos), 0.820435 (neg) | |
| data reader: epoch = 0, batch = 1140 / 4040 | |
| iter = 1140, cls_loss (cur) = 0.417243, cls_loss (avg) = 0.384619, lr = 0.010000 | |
| iter = 1140, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 1140, accuracy (avg) = 0.822831 (all), 0.826624 (pos), 0.820749 (neg) | |
| data reader: epoch = 0, batch = 1141 / 4040 | |
| iter = 1141, cls_loss (cur) = 0.445664, cls_loss (avg) = 0.385229, lr = 0.010000 | |
| iter = 1141, accuracy (cur) = 0.760000 (all), 0.640000 (pos), 0.880000 (neg) | |
| iter = 1141, accuracy (avg) = 0.822203 (all), 0.824758 (pos), 0.821341 (neg) | |
| data reader: epoch = 0, batch = 1142 / 4040 | |
| iter = 1142, cls_loss (cur) = 0.431087, cls_loss (avg) = 0.385688, lr = 0.010000 | |
| iter = 1142, accuracy (cur) = 0.760000 (all), 0.607143 (pos), 0.954545 (neg) | |
| iter = 1142, accuracy (avg) = 0.821581 (all), 0.822581 (pos), 0.822673 (neg) | |
| data reader: epoch = 0, batch = 1143 / 4040 | |
| iter = 1143, cls_loss (cur) = 0.329689, cls_loss (avg) = 0.385128, lr = 0.010000 | |
| iter = 1143, accuracy (cur) = 0.940000 (all), 0.896552 (pos), 1.000000 (neg) | |
| iter = 1143, accuracy (avg) = 0.822765 (all), 0.823321 (pos), 0.824447 (neg) | |
| data reader: epoch = 0, batch = 1144 / 4040 | |
| iter = 1144, cls_loss (cur) = 0.339324, cls_loss (avg) = 0.384670, lr = 0.010000 | |
| iter = 1144, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 1144, accuracy (avg) = 0.822737 (all), 0.823549 (pos), 0.824119 (neg) | |
| data reader: epoch = 0, batch = 1145 / 4040 | |
| iter = 1145, cls_loss (cur) = 0.514566, cls_loss (avg) = 0.385969, lr = 0.010000 | |
| iter = 1145, accuracy (cur) = 0.680000 (all), 0.720000 (pos), 0.640000 (neg) | |
| iter = 1145, accuracy (avg) = 0.821310 (all), 0.822514 (pos), 0.822278 (neg) | |
| data reader: epoch = 0, batch = 1146 / 4040 | |
| iter = 1146, cls_loss (cur) = 0.393724, cls_loss (avg) = 0.386046, lr = 0.010000 | |
| iter = 1146, accuracy (cur) = 0.800000 (all), 0.875000 (pos), 0.730769 (neg) | |
| iter = 1146, accuracy (avg) = 0.821097 (all), 0.823039 (pos), 0.821363 (neg) | |
| data reader: epoch = 0, batch = 1147 / 4040 | |
| iter = 1147, cls_loss (cur) = 0.285803, cls_loss (avg) = 0.385044, lr = 0.010000 | |
| iter = 1147, accuracy (cur) = 0.900000 (all), 0.772727 (pos), 1.000000 (neg) | |
| iter = 1147, accuracy (avg) = 0.821886 (all), 0.822536 (pos), 0.823149 (neg) | |
| data reader: epoch = 0, batch = 1148 / 4040 | |
| iter = 1148, cls_loss (cur) = 0.352543, cls_loss (avg) = 0.384719, lr = 0.010000 | |
| iter = 1148, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.827586 (neg) | |
| iter = 1148, accuracy (avg) = 0.822067 (all), 0.822882 (pos), 0.823193 (neg) | |
| data reader: epoch = 0, batch = 1149 / 4040 | |
| iter = 1149, cls_loss (cur) = 0.322182, cls_loss (avg) = 0.384094, lr = 0.010000 | |
| iter = 1149, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 1149, accuracy (avg) = 0.822446 (all), 0.823853 (pos), 0.822961 (neg) | |
| data reader: epoch = 0, batch = 1150 / 4040 | |
| iter = 1150, cls_loss (cur) = 0.280272, cls_loss (avg) = 0.383055, lr = 0.010000 | |
| iter = 1150, accuracy (cur) = 0.920000 (all), 0.950000 (pos), 0.900000 (neg) | |
| iter = 1150, accuracy (avg) = 0.823422 (all), 0.825114 (pos), 0.823732 (neg) | |
| data reader: epoch = 0, batch = 1151 / 4040 | |
| iter = 1151, cls_loss (cur) = 0.290979, cls_loss (avg) = 0.382135, lr = 0.010000 | |
| iter = 1151, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 1151, accuracy (avg) = 0.823988 (all), 0.825263 (pos), 0.824694 (neg) | |
| data reader: epoch = 0, batch = 1152 / 4040 | |
| iter = 1152, cls_loss (cur) = 0.250386, cls_loss (avg) = 0.380817, lr = 0.010000 | |
| iter = 1152, accuracy (cur) = 0.940000 (all), 0.920000 (pos), 0.960000 (neg) | |
| iter = 1152, accuracy (avg) = 0.825148 (all), 0.826211 (pos), 0.826048 (neg) | |
| data reader: epoch = 0, batch = 1153 / 4040 | |
| iter = 1153, cls_loss (cur) = 0.248598, cls_loss (avg) = 0.379495, lr = 0.010000 | |
| iter = 1153, accuracy (cur) = 0.900000 (all), 0.933333 (pos), 0.850000 (neg) | |
| iter = 1153, accuracy (avg) = 0.825896 (all), 0.827282 (pos), 0.826287 (neg) | |
| data reader: epoch = 0, batch = 1154 / 4040 | |
| iter = 1154, cls_loss (cur) = 0.359676, cls_loss (avg) = 0.379297, lr = 0.010000 | |
| iter = 1154, accuracy (cur) = 0.900000 (all), 0.904762 (pos), 0.896552 (neg) | |
| iter = 1154, accuracy (avg) = 0.826637 (all), 0.828057 (pos), 0.826990 (neg) | |
| data reader: epoch = 0, batch = 1155 / 4040 | |
| iter = 1155, cls_loss (cur) = 0.398288, cls_loss (avg) = 0.379487, lr = 0.010000 | |
| iter = 1155, accuracy (cur) = 0.800000 (all), 0.782609 (pos), 0.814815 (neg) | |
| iter = 1155, accuracy (avg) = 0.826371 (all), 0.827602 (pos), 0.826868 (neg) | |
| data reader: epoch = 0, batch = 1156 / 4040 | |
| iter = 1156, cls_loss (cur) = 0.450208, cls_loss (avg) = 0.380194, lr = 0.010000 | |
| iter = 1156, accuracy (cur) = 0.800000 (all), 0.695652 (pos), 0.888889 (neg) | |
| iter = 1156, accuracy (avg) = 0.826107 (all), 0.826283 (pos), 0.827488 (neg) | |
| data reader: epoch = 0, batch = 1157 / 4040 | |
| iter = 1157, cls_loss (cur) = 0.351692, cls_loss (avg) = 0.379909, lr = 0.010000 | |
| iter = 1157, accuracy (cur) = 0.840000 (all), 0.913043 (pos), 0.777778 (neg) | |
| iter = 1157, accuracy (avg) = 0.826246 (all), 0.827150 (pos), 0.826991 (neg) | |
| data reader: epoch = 0, batch = 1158 / 4040 | |
| iter = 1158, cls_loss (cur) = 0.221978, cls_loss (avg) = 0.378330, lr = 0.010000 | |
| iter = 1158, accuracy (cur) = 0.920000 (all), 0.920000 (pos), 0.920000 (neg) | |
| iter = 1158, accuracy (avg) = 0.827184 (all), 0.828079 (pos), 0.827921 (neg) | |
| data reader: epoch = 0, batch = 1159 / 4040 | |
| iter = 1159, cls_loss (cur) = 0.450775, cls_loss (avg) = 0.379054, lr = 0.010000 | |
| iter = 1159, accuracy (cur) = 0.800000 (all), 0.760000 (pos), 0.840000 (neg) | |
| iter = 1159, accuracy (avg) = 0.826912 (all), 0.827398 (pos), 0.828042 (neg) | |
| data reader: epoch = 0, batch = 1160 / 4040 | |
| iter = 1160, cls_loss (cur) = 0.346232, cls_loss (avg) = 0.378726, lr = 0.010000 | |
| iter = 1160, accuracy (cur) = 0.820000 (all), 0.722222 (pos), 0.875000 (neg) | |
| iter = 1160, accuracy (avg) = 0.826843 (all), 0.826346 (pos), 0.828512 (neg) | |
| data reader: epoch = 0, batch = 1161 / 4040 | |
| iter = 1161, cls_loss (cur) = 0.275966, cls_loss (avg) = 0.377698, lr = 0.010000 | |
| iter = 1161, accuracy (cur) = 0.920000 (all), 0.925926 (pos), 0.913043 (neg) | |
| iter = 1161, accuracy (avg) = 0.827774 (all), 0.827342 (pos), 0.829357 (neg) | |
| data reader: epoch = 0, batch = 1162 / 4040 | |
| iter = 1162, cls_loss (cur) = 0.466050, cls_loss (avg) = 0.378582, lr = 0.010000 | |
| iter = 1162, accuracy (cur) = 0.700000 (all), 0.653846 (pos), 0.750000 (neg) | |
| iter = 1162, accuracy (avg) = 0.826497 (all), 0.825607 (pos), 0.828563 (neg) | |
| data reader: epoch = 0, batch = 1163 / 4040 | |
| iter = 1163, cls_loss (cur) = 0.472692, cls_loss (avg) = 0.379523, lr = 0.010000 | |
| iter = 1163, accuracy (cur) = 0.760000 (all), 0.655172 (pos), 0.904762 (neg) | |
| iter = 1163, accuracy (avg) = 0.825832 (all), 0.823903 (pos), 0.829325 (neg) | |
| data reader: epoch = 0, batch = 1164 / 4040 | |
| iter = 1164, cls_loss (cur) = 0.294635, cls_loss (avg) = 0.378674, lr = 0.010000 | |
| iter = 1164, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 1164, accuracy (avg) = 0.826373 (all), 0.824553 (pos), 0.829728 (neg) | |
| data reader: epoch = 0, batch = 1165 / 4040 | |
| iter = 1165, cls_loss (cur) = 0.402351, cls_loss (avg) = 0.378911, lr = 0.010000 | |
| iter = 1165, accuracy (cur) = 0.820000 (all), 0.962963 (pos), 0.652174 (neg) | |
| iter = 1165, accuracy (avg) = 0.826310 (all), 0.825937 (pos), 0.827952 (neg) | |
| data reader: epoch = 0, batch = 1166 / 4040 | |
| iter = 1166, cls_loss (cur) = 0.258337, cls_loss (avg) = 0.377705, lr = 0.010000 | |
| iter = 1166, accuracy (cur) = 0.920000 (all), 0.920000 (pos), 0.920000 (neg) | |
| iter = 1166, accuracy (avg) = 0.827246 (all), 0.826877 (pos), 0.828873 (neg) | |
| data reader: epoch = 0, batch = 1167 / 4040 | |
| iter = 1167, cls_loss (cur) = 0.566428, cls_loss (avg) = 0.379592, lr = 0.010000 | |
| iter = 1167, accuracy (cur) = 0.700000 (all), 0.708333 (pos), 0.692308 (neg) | |
| iter = 1167, accuracy (avg) = 0.825974 (all), 0.825692 (pos), 0.827507 (neg) | |
| data reader: epoch = 0, batch = 1168 / 4040 | |
| iter = 1168, cls_loss (cur) = 0.303506, cls_loss (avg) = 0.378831, lr = 0.010000 | |
| iter = 1168, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.862069 (neg) | |
| iter = 1168, accuracy (avg) = 0.826914 (all), 0.827435 (pos), 0.827853 (neg) | |
| data reader: epoch = 0, batch = 1169 / 4040 | |
| iter = 1169, cls_loss (cur) = 0.359136, cls_loss (avg) = 0.378634, lr = 0.010000 | |
| iter = 1169, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 1169, accuracy (avg) = 0.827245 (all), 0.827679 (pos), 0.828270 (neg) | |
| data reader: epoch = 0, batch = 1170 / 4040 | |
| iter = 1170, cls_loss (cur) = 0.318956, cls_loss (avg) = 0.378038, lr = 0.010000 | |
| iter = 1170, accuracy (cur) = 0.900000 (all), 0.931034 (pos), 0.857143 (neg) | |
| iter = 1170, accuracy (avg) = 0.827973 (all), 0.828713 (pos), 0.828558 (neg) | |
| data reader: epoch = 0, batch = 1171 / 4040 | |
| iter = 1171, cls_loss (cur) = 0.386874, cls_loss (avg) = 0.378126, lr = 0.010000 | |
| iter = 1171, accuracy (cur) = 0.820000 (all), 0.863636 (pos), 0.785714 (neg) | |
| iter = 1171, accuracy (avg) = 0.827893 (all), 0.829062 (pos), 0.828130 (neg) | |
| data reader: epoch = 0, batch = 1172 / 4040 | |
| iter = 1172, cls_loss (cur) = 0.324671, cls_loss (avg) = 0.377591, lr = 0.010000 | |
| iter = 1172, accuracy (cur) = 0.920000 (all), 0.960000 (pos), 0.880000 (neg) | |
| iter = 1172, accuracy (avg) = 0.828814 (all), 0.830371 (pos), 0.828649 (neg) | |
| data reader: epoch = 0, batch = 1173 / 4040 | |
| iter = 1173, cls_loss (cur) = 0.294330, cls_loss (avg) = 0.376759, lr = 0.010000 | |
| iter = 1173, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.880000 (neg) | |
| iter = 1173, accuracy (avg) = 0.829926 (all), 0.832068 (pos), 0.829162 (neg) | |
| data reader: epoch = 0, batch = 1174 / 4040 | |
| iter = 1174, cls_loss (cur) = 0.409559, cls_loss (avg) = 0.377087, lr = 0.010000 | |
| iter = 1174, accuracy (cur) = 0.820000 (all), 0.842105 (pos), 0.806452 (neg) | |
| iter = 1174, accuracy (avg) = 0.829827 (all), 0.832168 (pos), 0.828935 (neg) | |
| data reader: epoch = 0, batch = 1175 / 4040 | |
| iter = 1175, cls_loss (cur) = 0.306237, cls_loss (avg) = 0.376378, lr = 0.010000 | |
| iter = 1175, accuracy (cur) = 0.900000 (all), 0.950000 (pos), 0.866667 (neg) | |
| iter = 1175, accuracy (avg) = 0.830528 (all), 0.833346 (pos), 0.829312 (neg) | |
| data reader: epoch = 0, batch = 1176 / 4040 | |
| iter = 1176, cls_loss (cur) = 0.438661, cls_loss (avg) = 0.377001, lr = 0.010000 | |
| iter = 1176, accuracy (cur) = 0.780000 (all), 0.772727 (pos), 0.785714 (neg) | |
| iter = 1176, accuracy (avg) = 0.830023 (all), 0.832740 (pos), 0.828876 (neg) | |
| data reader: epoch = 0, batch = 1177 / 4040 | |
| iter = 1177, cls_loss (cur) = 0.439065, cls_loss (avg) = 0.377622, lr = 0.010000 | |
| iter = 1177, accuracy (cur) = 0.840000 (all), 0.652174 (pos), 1.000000 (neg) | |
| iter = 1177, accuracy (avg) = 0.830123 (all), 0.830934 (pos), 0.830588 (neg) | |
| data reader: epoch = 0, batch = 1178 / 4040 | |
| iter = 1178, cls_loss (cur) = 0.241332, cls_loss (avg) = 0.376259, lr = 0.010000 | |
| iter = 1178, accuracy (cur) = 0.920000 (all), 0.954545 (pos), 0.892857 (neg) | |
| iter = 1178, accuracy (avg) = 0.831022 (all), 0.832171 (pos), 0.831210 (neg) | |
| data reader: epoch = 0, batch = 1179 / 4040 | |
| iter = 1179, cls_loss (cur) = 0.395976, cls_loss (avg) = 0.376456, lr = 0.010000 | |
| iter = 1179, accuracy (cur) = 0.820000 (all), 0.619048 (pos), 0.965517 (neg) | |
| iter = 1179, accuracy (avg) = 0.830911 (all), 0.830039 (pos), 0.832553 (neg) | |
| data reader: epoch = 0, batch = 1180 / 4040 | |
| iter = 1180, cls_loss (cur) = 0.407700, cls_loss (avg) = 0.376768, lr = 0.010000 | |
| iter = 1180, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 1180, accuracy (avg) = 0.830802 (all), 0.829596 (pos), 0.832864 (neg) | |
| data reader: epoch = 0, batch = 1181 / 4040 | |
| iter = 1181, cls_loss (cur) = 0.382103, cls_loss (avg) = 0.376822, lr = 0.010000 | |
| iter = 1181, accuracy (cur) = 0.820000 (all), 0.724138 (pos), 0.952381 (neg) | |
| iter = 1181, accuracy (avg) = 0.830694 (all), 0.828542 (pos), 0.834059 (neg) | |
| data reader: epoch = 0, batch = 1182 / 4040 | |
| iter = 1182, cls_loss (cur) = 0.314194, cls_loss (avg) = 0.376196, lr = 0.010000 | |
| iter = 1182, accuracy (cur) = 0.900000 (all), 0.925926 (pos), 0.869565 (neg) | |
| iter = 1182, accuracy (avg) = 0.831387 (all), 0.829515 (pos), 0.834414 (neg) | |
| data reader: epoch = 0, batch = 1183 / 4040 | |
| iter = 1183, cls_loss (cur) = 0.509695, cls_loss (avg) = 0.377531, lr = 0.010000 | |
| iter = 1183, accuracy (cur) = 0.780000 (all), 0.714286 (pos), 0.863636 (neg) | |
| iter = 1183, accuracy (avg) = 0.830873 (all), 0.828363 (pos), 0.834707 (neg) | |
| data reader: epoch = 0, batch = 1184 / 4040 | |
| iter = 1184, cls_loss (cur) = 0.334457, cls_loss (avg) = 0.377100, lr = 0.010000 | |
| iter = 1184, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 1184, accuracy (avg) = 0.831365 (all), 0.829008 (pos), 0.834996 (neg) | |
| data reader: epoch = 0, batch = 1185 / 4040 | |
| iter = 1185, cls_loss (cur) = 0.265209, cls_loss (avg) = 0.375981, lr = 0.010000 | |
| iter = 1185, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 1185, accuracy (avg) = 0.831851 (all), 0.829646 (pos), 0.835282 (neg) | |
| data reader: epoch = 0, batch = 1186 / 4040 | |
| iter = 1186, cls_loss (cur) = 0.363473, cls_loss (avg) = 0.375856, lr = 0.010000 | |
| iter = 1186, accuracy (cur) = 0.800000 (all), 0.909091 (pos), 0.714286 (neg) | |
| iter = 1186, accuracy (avg) = 0.831533 (all), 0.830441 (pos), 0.834072 (neg) | |
| data reader: epoch = 0, batch = 1187 / 4040 | |
| iter = 1187, cls_loss (cur) = 0.377633, cls_loss (avg) = 0.375874, lr = 0.010000 | |
| iter = 1187, accuracy (cur) = 0.840000 (all), 0.928571 (pos), 0.727273 (neg) | |
| iter = 1187, accuracy (avg) = 0.831617 (all), 0.831422 (pos), 0.833004 (neg) | |
| data reader: epoch = 0, batch = 1188 / 4040 | |
| iter = 1188, cls_loss (cur) = 0.450973, cls_loss (avg) = 0.376625, lr = 0.010000 | |
| iter = 1188, accuracy (cur) = 0.780000 (all), 0.894737 (pos), 0.709677 (neg) | |
| iter = 1188, accuracy (avg) = 0.831101 (all), 0.832055 (pos), 0.831771 (neg) | |
| data reader: epoch = 0, batch = 1189 / 4040 | |
| iter = 1189, cls_loss (cur) = 0.333482, cls_loss (avg) = 0.376193, lr = 0.010000 | |
| iter = 1189, accuracy (cur) = 0.820000 (all), 0.916667 (pos), 0.730769 (neg) | |
| iter = 1189, accuracy (avg) = 0.830990 (all), 0.832902 (pos), 0.830761 (neg) | |
| data reader: epoch = 0, batch = 1190 / 4040 | |
| iter = 1190, cls_loss (cur) = 0.353027, cls_loss (avg) = 0.375962, lr = 0.010000 | |
| iter = 1190, accuracy (cur) = 0.840000 (all), 0.916667 (pos), 0.769231 (neg) | |
| iter = 1190, accuracy (avg) = 0.831080 (all), 0.833739 (pos), 0.830146 (neg) | |
| data reader: epoch = 0, batch = 1191 / 4040 | |
| iter = 1191, cls_loss (cur) = 0.490934, cls_loss (avg) = 0.377111, lr = 0.010000 | |
| iter = 1191, accuracy (cur) = 0.760000 (all), 0.826087 (pos), 0.703704 (neg) | |
| iter = 1191, accuracy (avg) = 0.830369 (all), 0.833663 (pos), 0.828881 (neg) | |
| data reader: epoch = 0, batch = 1192 / 4040 | |
| iter = 1192, cls_loss (cur) = 0.461033, cls_loss (avg) = 0.377950, lr = 0.010000 | |
| iter = 1192, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.857143 (neg) | |
| iter = 1192, accuracy (avg) = 0.830066 (all), 0.832599 (pos), 0.829164 (neg) | |
| data reader: epoch = 0, batch = 1193 / 4040 | |
| iter = 1193, cls_loss (cur) = 0.308282, cls_loss (avg) = 0.377254, lr = 0.010000 | |
| iter = 1193, accuracy (cur) = 0.900000 (all), 0.833333 (pos), 0.961538 (neg) | |
| iter = 1193, accuracy (avg) = 0.830765 (all), 0.832606 (pos), 0.830488 (neg) | |
| data reader: epoch = 0, batch = 1194 / 4040 | |
| iter = 1194, cls_loss (cur) = 0.477406, cls_loss (avg) = 0.378255, lr = 0.010000 | |
| iter = 1194, accuracy (cur) = 0.760000 (all), 0.583333 (pos), 0.923077 (neg) | |
| iter = 1194, accuracy (avg) = 0.830057 (all), 0.830113 (pos), 0.831414 (neg) | |
| data reader: epoch = 0, batch = 1195 / 4040 | |
| iter = 1195, cls_loss (cur) = 0.258563, cls_loss (avg) = 0.377058, lr = 0.010000 | |
| iter = 1195, accuracy (cur) = 0.940000 (all), 0.913043 (pos), 0.962963 (neg) | |
| iter = 1195, accuracy (avg) = 0.831157 (all), 0.830943 (pos), 0.832729 (neg) | |
| data reader: epoch = 0, batch = 1196 / 4040 | |
| iter = 1196, cls_loss (cur) = 0.388018, cls_loss (avg) = 0.377168, lr = 0.010000 | |
| iter = 1196, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 1196, accuracy (avg) = 0.831245 (all), 0.830550 (pos), 0.833248 (neg) | |
| data reader: epoch = 0, batch = 1197 / 4040 | |
| iter = 1197, cls_loss (cur) = 0.384701, cls_loss (avg) = 0.377243, lr = 0.010000 | |
| iter = 1197, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.818182 (neg) | |
| iter = 1197, accuracy (avg) = 0.831333 (all), 0.830816 (pos), 0.833097 (neg) | |
| data reader: epoch = 0, batch = 1198 / 4040 | |
| iter = 1198, cls_loss (cur) = 0.340301, cls_loss (avg) = 0.376874, lr = 0.010000 | |
| iter = 1198, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.900000 (neg) | |
| iter = 1198, accuracy (avg) = 0.831419 (all), 0.830008 (pos), 0.833766 (neg) | |
| data reader: epoch = 0, batch = 1199 / 4040 | |
| iter = 1199, cls_loss (cur) = 0.296999, cls_loss (avg) = 0.376075, lr = 0.010000 | |
| iter = 1199, accuracy (cur) = 0.940000 (all), 0.944444 (pos), 0.937500 (neg) | |
| iter = 1199, accuracy (avg) = 0.832505 (all), 0.831152 (pos), 0.834804 (neg) | |
| data reader: epoch = 0, batch = 1200 / 4040 | |
| iter = 1200, cls_loss (cur) = 0.385640, cls_loss (avg) = 0.376171, lr = 0.010000 | |
| iter = 1200, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 1200, accuracy (avg) = 0.832380 (all), 0.830757 (pos), 0.834917 (neg) | |
| data reader: epoch = 0, batch = 1201 / 4040 | |
| iter = 1201, cls_loss (cur) = 0.386485, cls_loss (avg) = 0.376274, lr = 0.010000 | |
| iter = 1201, accuracy (cur) = 0.880000 (all), 0.838710 (pos), 0.947368 (neg) | |
| iter = 1201, accuracy (avg) = 0.832856 (all), 0.830837 (pos), 0.836042 (neg) | |
| data reader: epoch = 0, batch = 1202 / 4040 | |
| iter = 1202, cls_loss (cur) = 0.319808, cls_loss (avg) = 0.375709, lr = 0.010000 | |
| iter = 1202, accuracy (cur) = 0.840000 (all), 0.769231 (pos), 0.916667 (neg) | |
| iter = 1202, accuracy (avg) = 0.832928 (all), 0.830221 (pos), 0.836848 (neg) | |
| data reader: epoch = 0, batch = 1203 / 4040 | |
| iter = 1203, cls_loss (cur) = 0.512409, cls_loss (avg) = 0.377076, lr = 0.010000 | |
| iter = 1203, accuracy (cur) = 0.780000 (all), 0.846154 (pos), 0.708333 (neg) | |
| iter = 1203, accuracy (avg) = 0.832398 (all), 0.830380 (pos), 0.835563 (neg) | |
| data reader: epoch = 0, batch = 1204 / 4040 | |
| iter = 1204, cls_loss (cur) = 0.340976, cls_loss (avg) = 0.376715, lr = 0.010000 | |
| iter = 1204, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1204, accuracy (avg) = 0.832675 (all), 0.830876 (pos), 0.835607 (neg) | |
| data reader: epoch = 0, batch = 1205 / 4040 | |
| iter = 1205, cls_loss (cur) = 0.420928, cls_loss (avg) = 0.377157, lr = 0.010000 | |
| iter = 1205, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 1205, accuracy (avg) = 0.832748 (all), 0.831414 (pos), 0.835168 (neg) | |
| data reader: epoch = 0, batch = 1206 / 4040 | |
| iter = 1206, cls_loss (cur) = 0.342767, cls_loss (avg) = 0.376814, lr = 0.010000 | |
| iter = 1206, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 1206, accuracy (avg) = 0.832420 (all), 0.831099 (pos), 0.834816 (neg) | |
| data reader: epoch = 0, batch = 1207 / 4040 | |
| iter = 1207, cls_loss (cur) = 0.418531, cls_loss (avg) = 0.377231, lr = 0.010000 | |
| iter = 1207, accuracy (cur) = 0.780000 (all), 0.875000 (pos), 0.692308 (neg) | |
| iter = 1207, accuracy (avg) = 0.831896 (all), 0.831538 (pos), 0.833391 (neg) | |
| data reader: epoch = 0, batch = 1208 / 4040 | |
| iter = 1208, cls_loss (cur) = 0.268816, cls_loss (avg) = 0.376147, lr = 0.010000 | |
| iter = 1208, accuracy (cur) = 0.900000 (all), 0.954545 (pos), 0.857143 (neg) | |
| iter = 1208, accuracy (avg) = 0.832577 (all), 0.832769 (pos), 0.833629 (neg) | |
| data reader: epoch = 0, batch = 1209 / 4040 | |
| iter = 1209, cls_loss (cur) = 0.392509, cls_loss (avg) = 0.376310, lr = 0.010000 | |
| iter = 1209, accuracy (cur) = 0.840000 (all), 0.862069 (pos), 0.809524 (neg) | |
| iter = 1209, accuracy (avg) = 0.832651 (all), 0.833062 (pos), 0.833388 (neg) | |
| data reader: epoch = 0, batch = 1210 / 4040 | |
| iter = 1210, cls_loss (cur) = 0.430014, cls_loss (avg) = 0.376847, lr = 0.010000 | |
| iter = 1210, accuracy (cur) = 0.780000 (all), 0.782609 (pos), 0.777778 (neg) | |
| iter = 1210, accuracy (avg) = 0.832125 (all), 0.832557 (pos), 0.832831 (neg) | |
| data reader: epoch = 0, batch = 1211 / 4040 | |
| iter = 1211, cls_loss (cur) = 0.337778, cls_loss (avg) = 0.376457, lr = 0.010000 | |
| iter = 1211, accuracy (cur) = 0.860000 (all), 0.821429 (pos), 0.909091 (neg) | |
| iter = 1211, accuracy (avg) = 0.832404 (all), 0.832446 (pos), 0.833594 (neg) | |
| data reader: epoch = 0, batch = 1212 / 4040 | |
| iter = 1212, cls_loss (cur) = 0.358577, cls_loss (avg) = 0.376278, lr = 0.010000 | |
| iter = 1212, accuracy (cur) = 0.840000 (all), 0.894737 (pos), 0.806452 (neg) | |
| iter = 1212, accuracy (avg) = 0.832480 (all), 0.833069 (pos), 0.833323 (neg) | |
| data reader: epoch = 0, batch = 1213 / 4040 | |
| iter = 1213, cls_loss (cur) = 0.438487, cls_loss (avg) = 0.376900, lr = 0.010000 | |
| iter = 1213, accuracy (cur) = 0.840000 (all), 0.862069 (pos), 0.809524 (neg) | |
| iter = 1213, accuracy (avg) = 0.832555 (all), 0.833359 (pos), 0.833085 (neg) | |
| data reader: epoch = 0, batch = 1214 / 4040 | |
| iter = 1214, cls_loss (cur) = 0.387845, cls_loss (avg) = 0.377009, lr = 0.010000 | |
| iter = 1214, accuracy (cur) = 0.860000 (all), 0.821429 (pos), 0.909091 (neg) | |
| iter = 1214, accuracy (avg) = 0.832829 (all), 0.833239 (pos), 0.833845 (neg) | |
| data reader: epoch = 0, batch = 1215 / 4040 | |
| iter = 1215, cls_loss (cur) = 0.394380, cls_loss (avg) = 0.377183, lr = 0.010000 | |
| iter = 1215, accuracy (cur) = 0.800000 (all), 0.739130 (pos), 0.851852 (neg) | |
| iter = 1215, accuracy (avg) = 0.832501 (all), 0.832298 (pos), 0.834025 (neg) | |
| data reader: epoch = 0, batch = 1216 / 4040 | |
| iter = 1216, cls_loss (cur) = 0.404732, cls_loss (avg) = 0.377458, lr = 0.010000 | |
| iter = 1216, accuracy (cur) = 0.860000 (all), 0.916667 (pos), 0.714286 (neg) | |
| iter = 1216, accuracy (avg) = 0.832776 (all), 0.833142 (pos), 0.832827 (neg) | |
| data reader: epoch = 0, batch = 1217 / 4040 | |
| iter = 1217, cls_loss (cur) = 0.334910, cls_loss (avg) = 0.377033, lr = 0.010000 | |
| iter = 1217, accuracy (cur) = 0.900000 (all), 0.896552 (pos), 0.904762 (neg) | |
| iter = 1217, accuracy (avg) = 0.833448 (all), 0.833776 (pos), 0.833547 (neg) | |
| data reader: epoch = 0, batch = 1218 / 4040 | |
| iter = 1218, cls_loss (cur) = 0.412589, cls_loss (avg) = 0.377389, lr = 0.010000 | |
| iter = 1218, accuracy (cur) = 0.760000 (all), 0.913043 (pos), 0.629630 (neg) | |
| iter = 1218, accuracy (avg) = 0.832714 (all), 0.834569 (pos), 0.831508 (neg) | |
| data reader: epoch = 0, batch = 1219 / 4040 | |
| iter = 1219, cls_loss (cur) = 0.529601, cls_loss (avg) = 0.378911, lr = 0.010000 | |
| iter = 1219, accuracy (cur) = 0.700000 (all), 0.793103 (pos), 0.571429 (neg) | |
| iter = 1219, accuracy (avg) = 0.831387 (all), 0.834154 (pos), 0.828907 (neg) | |
| data reader: epoch = 0, batch = 1220 / 4040 | |
| iter = 1220, cls_loss (cur) = 0.385686, cls_loss (avg) = 0.378978, lr = 0.010000 | |
| iter = 1220, accuracy (cur) = 0.780000 (all), 0.892857 (pos), 0.636364 (neg) | |
| iter = 1220, accuracy (avg) = 0.830873 (all), 0.834741 (pos), 0.826981 (neg) | |
| data reader: epoch = 0, batch = 1221 / 4040 | |
| iter = 1221, cls_loss (cur) = 0.271734, cls_loss (avg) = 0.377906, lr = 0.010000 | |
| iter = 1221, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.880000 (neg) | |
| iter = 1221, accuracy (avg) = 0.831964 (all), 0.836394 (pos), 0.827511 (neg) | |
| data reader: epoch = 0, batch = 1222 / 4040 | |
| iter = 1222, cls_loss (cur) = 0.314569, cls_loss (avg) = 0.377273, lr = 0.010000 | |
| iter = 1222, accuracy (cur) = 0.880000 (all), 0.960000 (pos), 0.800000 (neg) | |
| iter = 1222, accuracy (avg) = 0.832444 (all), 0.837630 (pos), 0.827236 (neg) | |
| data reader: epoch = 0, batch = 1223 / 4040 | |
| iter = 1223, cls_loss (cur) = 0.456998, cls_loss (avg) = 0.378070, lr = 0.010000 | |
| iter = 1223, accuracy (cur) = 0.760000 (all), 0.814815 (pos), 0.695652 (neg) | |
| iter = 1223, accuracy (avg) = 0.831720 (all), 0.837402 (pos), 0.825921 (neg) | |
| data reader: epoch = 0, batch = 1224 / 4040 | |
| iter = 1224, cls_loss (cur) = 0.277987, cls_loss (avg) = 0.377069, lr = 0.010000 | |
| iter = 1224, accuracy (cur) = 0.920000 (all), 0.869565 (pos), 0.962963 (neg) | |
| iter = 1224, accuracy (avg) = 0.832603 (all), 0.837723 (pos), 0.827291 (neg) | |
| data reader: epoch = 0, batch = 1225 / 4040 | |
| iter = 1225, cls_loss (cur) = 0.438203, cls_loss (avg) = 0.377680, lr = 0.010000 | |
| iter = 1225, accuracy (cur) = 0.760000 (all), 0.793103 (pos), 0.714286 (neg) | |
| iter = 1225, accuracy (avg) = 0.831877 (all), 0.837277 (pos), 0.826161 (neg) | |
| data reader: epoch = 0, batch = 1226 / 4040 | |
| iter = 1226, cls_loss (cur) = 0.434147, cls_loss (avg) = 0.378245, lr = 0.010000 | |
| iter = 1226, accuracy (cur) = 0.800000 (all), 0.851852 (pos), 0.739130 (neg) | |
| iter = 1226, accuracy (avg) = 0.831558 (all), 0.837423 (pos), 0.825291 (neg) | |
| data reader: epoch = 0, batch = 1227 / 4040 | |
| iter = 1227, cls_loss (cur) = 0.271536, cls_loss (avg) = 0.377178, lr = 0.010000 | |
| iter = 1227, accuracy (cur) = 0.900000 (all), 0.894737 (pos), 0.903226 (neg) | |
| iter = 1227, accuracy (avg) = 0.832242 (all), 0.837996 (pos), 0.826070 (neg) | |
| data reader: epoch = 0, batch = 1228 / 4040 | |
| iter = 1228, cls_loss (cur) = 0.302717, cls_loss (avg) = 0.376433, lr = 0.010000 | |
| iter = 1228, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.906250 (neg) | |
| iter = 1228, accuracy (avg) = 0.832720 (all), 0.837949 (pos), 0.826872 (neg) | |
| data reader: epoch = 0, batch = 1229 / 4040 | |
| iter = 1229, cls_loss (cur) = 0.404431, cls_loss (avg) = 0.376713, lr = 0.010000 | |
| iter = 1229, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1229, accuracy (avg) = 0.832993 (all), 0.838320 (pos), 0.827065 (neg) | |
| data reader: epoch = 0, batch = 1230 / 4040 | |
| iter = 1230, cls_loss (cur) = 0.307448, cls_loss (avg) = 0.376021, lr = 0.010000 | |
| iter = 1230, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 1230, accuracy (avg) = 0.833463 (all), 0.838737 (pos), 0.827594 (neg) | |
| data reader: epoch = 0, batch = 1231 / 4040 | |
| iter = 1231, cls_loss (cur) = 0.370611, cls_loss (avg) = 0.375967, lr = 0.010000 | |
| iter = 1231, accuracy (cur) = 0.860000 (all), 0.818182 (pos), 0.941176 (neg) | |
| iter = 1231, accuracy (avg) = 0.833728 (all), 0.838531 (pos), 0.828730 (neg) | |
| data reader: epoch = 0, batch = 1232 / 4040 | |
| iter = 1232, cls_loss (cur) = 0.419400, cls_loss (avg) = 0.376401, lr = 0.010000 | |
| iter = 1232, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.769231 (neg) | |
| iter = 1232, accuracy (avg) = 0.833391 (all), 0.838479 (pos), 0.828135 (neg) | |
| data reader: epoch = 0, batch = 1233 / 4040 | |
| iter = 1233, cls_loss (cur) = 0.259170, cls_loss (avg) = 0.375229, lr = 0.010000 | |
| iter = 1233, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 1233, accuracy (avg) = 0.834057 (all), 0.839185 (pos), 0.828782 (neg) | |
| data reader: epoch = 0, batch = 1234 / 4040 | |
| iter = 1234, cls_loss (cur) = 0.243816, cls_loss (avg) = 0.373914, lr = 0.010000 | |
| iter = 1234, accuracy (cur) = 0.920000 (all), 0.966667 (pos), 0.850000 (neg) | |
| iter = 1234, accuracy (avg) = 0.834916 (all), 0.840460 (pos), 0.828994 (neg) | |
| data reader: epoch = 0, batch = 1235 / 4040 | |
| iter = 1235, cls_loss (cur) = 0.354734, cls_loss (avg) = 0.373723, lr = 0.010000 | |
| iter = 1235, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 1235, accuracy (avg) = 0.835167 (all), 0.840944 (pos), 0.828965 (neg) | |
| data reader: epoch = 0, batch = 1236 / 4040 | |
| iter = 1236, cls_loss (cur) = 0.388317, cls_loss (avg) = 0.373869, lr = 0.010000 | |
| iter = 1236, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1236, accuracy (avg) = 0.835416 (all), 0.841463 (pos), 0.828857 (neg) | |
| data reader: epoch = 0, batch = 1237 / 4040 | |
| iter = 1237, cls_loss (cur) = 0.340062, cls_loss (avg) = 0.373531, lr = 0.010000 | |
| iter = 1237, accuracy (cur) = 0.780000 (all), 0.789474 (pos), 0.774194 (neg) | |
| iter = 1237, accuracy (avg) = 0.834861 (all), 0.840944 (pos), 0.828311 (neg) | |
| data reader: epoch = 0, batch = 1238 / 4040 | |
| iter = 1238, cls_loss (cur) = 0.289519, cls_loss (avg) = 0.372690, lr = 0.010000 | |
| iter = 1238, accuracy (cur) = 0.900000 (all), 0.931034 (pos), 0.857143 (neg) | |
| iter = 1238, accuracy (avg) = 0.835513 (all), 0.841844 (pos), 0.828599 (neg) | |
| data reader: epoch = 0, batch = 1239 / 4040 | |
| iter = 1239, cls_loss (cur) = 0.268231, cls_loss (avg) = 0.371646, lr = 0.010000 | |
| iter = 1239, accuracy (cur) = 0.920000 (all), 0.954545 (pos), 0.892857 (neg) | |
| iter = 1239, accuracy (avg) = 0.836358 (all), 0.842971 (pos), 0.829242 (neg) | |
| data reader: epoch = 0, batch = 1240 / 4040 | |
| iter = 1240, cls_loss (cur) = 0.429655, cls_loss (avg) = 0.372226, lr = 0.010000 | |
| iter = 1240, accuracy (cur) = 0.840000 (all), 0.736842 (pos), 0.903226 (neg) | |
| iter = 1240, accuracy (avg) = 0.836394 (all), 0.841910 (pos), 0.829981 (neg) | |
| data reader: epoch = 0, batch = 1241 / 4040 | |
| iter = 1241, cls_loss (cur) = 0.390630, cls_loss (avg) = 0.372410, lr = 0.010000 | |
| iter = 1241, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 1241, accuracy (avg) = 0.836430 (all), 0.841422 (pos), 0.830729 (neg) | |
| data reader: epoch = 0, batch = 1242 / 4040 | |
| iter = 1242, cls_loss (cur) = 0.400300, cls_loss (avg) = 0.372689, lr = 0.010000 | |
| iter = 1242, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 1242, accuracy (avg) = 0.836266 (all), 0.841222 (pos), 0.830604 (neg) | |
| data reader: epoch = 0, batch = 1243 / 4040 | |
| iter = 1243, cls_loss (cur) = 0.421951, cls_loss (avg) = 0.373181, lr = 0.010000 | |
| iter = 1243, accuracy (cur) = 0.760000 (all), 0.724138 (pos), 0.809524 (neg) | |
| iter = 1243, accuracy (avg) = 0.835503 (all), 0.840051 (pos), 0.830393 (neg) | |
| data reader: epoch = 0, batch = 1244 / 4040 | |
| iter = 1244, cls_loss (cur) = 0.485407, cls_loss (avg) = 0.374304, lr = 0.010000 | |
| iter = 1244, accuracy (cur) = 0.780000 (all), 0.625000 (pos), 0.923077 (neg) | |
| iter = 1244, accuracy (avg) = 0.834948 (all), 0.837901 (pos), 0.831320 (neg) | |
| data reader: epoch = 0, batch = 1245 / 4040 | |
| iter = 1245, cls_loss (cur) = 0.409897, cls_loss (avg) = 0.374660, lr = 0.010000 | |
| iter = 1245, accuracy (cur) = 0.840000 (all), 0.777778 (pos), 0.913043 (neg) | |
| iter = 1245, accuracy (avg) = 0.834999 (all), 0.837300 (pos), 0.832137 (neg) | |
| data reader: epoch = 0, batch = 1246 / 4040 | |
| iter = 1246, cls_loss (cur) = 0.494454, cls_loss (avg) = 0.375858, lr = 0.010000 | |
| iter = 1246, accuracy (cur) = 0.760000 (all), 0.888889 (pos), 0.608696 (neg) | |
| iter = 1246, accuracy (avg) = 0.834249 (all), 0.837815 (pos), 0.829903 (neg) | |
| data reader: epoch = 0, batch = 1247 / 4040 | |
| iter = 1247, cls_loss (cur) = 0.426324, cls_loss (avg) = 0.376362, lr = 0.010000 | |
| iter = 1247, accuracy (cur) = 0.740000 (all), 0.739130 (pos), 0.740741 (neg) | |
| iter = 1247, accuracy (avg) = 0.833306 (all), 0.836829 (pos), 0.829011 (neg) | |
| data reader: epoch = 0, batch = 1248 / 4040 | |
| iter = 1248, cls_loss (cur) = 0.406856, cls_loss (avg) = 0.376667, lr = 0.010000 | |
| iter = 1248, accuracy (cur) = 0.820000 (all), 0.851852 (pos), 0.782609 (neg) | |
| iter = 1248, accuracy (avg) = 0.833173 (all), 0.836979 (pos), 0.828547 (neg) | |
| data reader: epoch = 0, batch = 1249 / 4040 | |
| iter = 1249, cls_loss (cur) = 0.372157, cls_loss (avg) = 0.376622, lr = 0.010000 | |
| iter = 1249, accuracy (cur) = 0.780000 (all), 0.821429 (pos), 0.727273 (neg) | |
| iter = 1249, accuracy (avg) = 0.832641 (all), 0.836823 (pos), 0.827534 (neg) | |
| data reader: epoch = 0, batch = 1250 / 4040 | |
| iter = 1250, cls_loss (cur) = 0.614647, cls_loss (avg) = 0.379002, lr = 0.010000 | |
| iter = 1250, accuracy (cur) = 0.660000 (all), 0.619048 (pos), 0.689655 (neg) | |
| iter = 1250, accuracy (avg) = 0.830915 (all), 0.834646 (pos), 0.826155 (neg) | |
| data reader: epoch = 0, batch = 1251 / 4040 | |
| iter = 1251, cls_loss (cur) = 0.425837, cls_loss (avg) = 0.379471, lr = 0.010000 | |
| iter = 1251, accuracy (cur) = 0.780000 (all), 0.818182 (pos), 0.750000 (neg) | |
| iter = 1251, accuracy (avg) = 0.830406 (all), 0.834481 (pos), 0.825394 (neg) | |
| data reader: epoch = 0, batch = 1252 / 4040 | |
| iter = 1252, cls_loss (cur) = 0.360779, cls_loss (avg) = 0.379284, lr = 0.010000 | |
| iter = 1252, accuracy (cur) = 0.860000 (all), 0.714286 (pos), 0.916667 (neg) | |
| iter = 1252, accuracy (avg) = 0.830702 (all), 0.833279 (pos), 0.826307 (neg) | |
| data reader: epoch = 0, batch = 1253 / 4040 | |
| iter = 1253, cls_loss (cur) = 0.290206, cls_loss (avg) = 0.378393, lr = 0.010000 | |
| iter = 1253, accuracy (cur) = 0.900000 (all), 0.851852 (pos), 0.956522 (neg) | |
| iter = 1253, accuracy (avg) = 0.831395 (all), 0.833465 (pos), 0.827609 (neg) | |
| data reader: epoch = 0, batch = 1254 / 4040 | |
| iter = 1254, cls_loss (cur) = 0.295190, cls_loss (avg) = 0.377561, lr = 0.010000 | |
| iter = 1254, accuracy (cur) = 0.900000 (all), 0.818182 (pos), 0.964286 (neg) | |
| iter = 1254, accuracy (avg) = 0.832081 (all), 0.833312 (pos), 0.828975 (neg) | |
| data reader: epoch = 0, batch = 1255 / 4040 | |
| iter = 1255, cls_loss (cur) = 0.355885, cls_loss (avg) = 0.377344, lr = 0.010000 | |
| iter = 1255, accuracy (cur) = 0.860000 (all), 0.769231 (pos), 0.958333 (neg) | |
| iter = 1255, accuracy (avg) = 0.832360 (all), 0.832671 (pos), 0.830269 (neg) | |
| data reader: epoch = 0, batch = 1256 / 4040 | |
| iter = 1256, cls_loss (cur) = 0.376393, cls_loss (avg) = 0.377335, lr = 0.010000 | |
| iter = 1256, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 1256, accuracy (avg) = 0.832636 (all), 0.832965 (pos), 0.830538 (neg) | |
| data reader: epoch = 0, batch = 1257 / 4040 | |
| iter = 1257, cls_loss (cur) = 0.427014, cls_loss (avg) = 0.377831, lr = 0.010000 | |
| iter = 1257, accuracy (cur) = 0.760000 (all), 0.741935 (pos), 0.789474 (neg) | |
| iter = 1257, accuracy (avg) = 0.831910 (all), 0.832055 (pos), 0.830127 (neg) | |
| data reader: epoch = 0, batch = 1258 / 4040 | |
| iter = 1258, cls_loss (cur) = 0.522087, cls_loss (avg) = 0.379274, lr = 0.010000 | |
| iter = 1258, accuracy (cur) = 0.780000 (all), 0.826087 (pos), 0.740741 (neg) | |
| iter = 1258, accuracy (avg) = 0.831391 (all), 0.831995 (pos), 0.829233 (neg) | |
| data reader: epoch = 0, batch = 1259 / 4040 | |
| iter = 1259, cls_loss (cur) = 0.358862, cls_loss (avg) = 0.379070, lr = 0.010000 | |
| iter = 1259, accuracy (cur) = 0.800000 (all), 0.821429 (pos), 0.772727 (neg) | |
| iter = 1259, accuracy (avg) = 0.831077 (all), 0.831889 (pos), 0.828668 (neg) | |
| data reader: epoch = 0, batch = 1260 / 4040 | |
| iter = 1260, cls_loss (cur) = 0.369953, cls_loss (avg) = 0.378979, lr = 0.010000 | |
| iter = 1260, accuracy (cur) = 0.900000 (all), 0.967742 (pos), 0.789474 (neg) | |
| iter = 1260, accuracy (avg) = 0.831766 (all), 0.833248 (pos), 0.828276 (neg) | |
| data reader: epoch = 0, batch = 1261 / 4040 | |
| iter = 1261, cls_loss (cur) = 0.382605, cls_loss (avg) = 0.379015, lr = 0.010000 | |
| iter = 1261, accuracy (cur) = 0.800000 (all), 0.888889 (pos), 0.695652 (neg) | |
| iter = 1261, accuracy (avg) = 0.831449 (all), 0.833804 (pos), 0.826950 (neg) | |
| data reader: epoch = 0, batch = 1262 / 4040 | |
| iter = 1262, cls_loss (cur) = 0.406530, cls_loss (avg) = 0.379290, lr = 0.010000 | |
| iter = 1262, accuracy (cur) = 0.760000 (all), 0.916667 (pos), 0.615385 (neg) | |
| iter = 1262, accuracy (avg) = 0.830734 (all), 0.834633 (pos), 0.824834 (neg) | |
| data reader: epoch = 0, batch = 1263 / 4040 | |
| iter = 1263, cls_loss (cur) = 0.324600, cls_loss (avg) = 0.378743, lr = 0.010000 | |
| iter = 1263, accuracy (cur) = 0.860000 (all), 0.916667 (pos), 0.807692 (neg) | |
| iter = 1263, accuracy (avg) = 0.831027 (all), 0.835453 (pos), 0.824663 (neg) | |
| data reader: epoch = 0, batch = 1264 / 4040 | |
| iter = 1264, cls_loss (cur) = 0.452373, cls_loss (avg) = 0.379480, lr = 0.010000 | |
| iter = 1264, accuracy (cur) = 0.780000 (all), 0.741935 (pos), 0.842105 (neg) | |
| iter = 1264, accuracy (avg) = 0.830516 (all), 0.834518 (pos), 0.824837 (neg) | |
| data reader: epoch = 0, batch = 1265 / 4040 | |
| iter = 1265, cls_loss (cur) = 0.347510, cls_loss (avg) = 0.379160, lr = 0.010000 | |
| iter = 1265, accuracy (cur) = 0.860000 (all), 0.956522 (pos), 0.777778 (neg) | |
| iter = 1265, accuracy (avg) = 0.830811 (all), 0.835738 (pos), 0.824367 (neg) | |
| data reader: epoch = 0, batch = 1266 / 4040 | |
| iter = 1266, cls_loss (cur) = 0.400263, cls_loss (avg) = 0.379371, lr = 0.010000 | |
| iter = 1266, accuracy (cur) = 0.860000 (all), 0.884615 (pos), 0.833333 (neg) | |
| iter = 1266, accuracy (avg) = 0.831103 (all), 0.836227 (pos), 0.824456 (neg) | |
| data reader: epoch = 0, batch = 1267 / 4040 | |
| iter = 1267, cls_loss (cur) = 0.359129, cls_loss (avg) = 0.379168, lr = 0.010000 | |
| iter = 1267, accuracy (cur) = 0.820000 (all), 0.840000 (pos), 0.800000 (neg) | |
| iter = 1267, accuracy (avg) = 0.830992 (all), 0.836265 (pos), 0.824212 (neg) | |
| data reader: epoch = 0, batch = 1268 / 4040 | |
| iter = 1268, cls_loss (cur) = 0.417547, cls_loss (avg) = 0.379552, lr = 0.010000 | |
| iter = 1268, accuracy (cur) = 0.760000 (all), 0.843750 (pos), 0.611111 (neg) | |
| iter = 1268, accuracy (avg) = 0.830282 (all), 0.836340 (pos), 0.822081 (neg) | |
| data reader: epoch = 0, batch = 1269 / 4040 | |
| iter = 1269, cls_loss (cur) = 0.248158, cls_loss (avg) = 0.378238, lr = 0.010000 | |
| iter = 1269, accuracy (cur) = 0.940000 (all), 0.933333 (pos), 0.950000 (neg) | |
| iter = 1269, accuracy (avg) = 0.831379 (all), 0.837309 (pos), 0.823360 (neg) | |
| data reader: epoch = 0, batch = 1270 / 4040 | |
| iter = 1270, cls_loss (cur) = 0.357747, cls_loss (avg) = 0.378033, lr = 0.010000 | |
| iter = 1270, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 1270, accuracy (avg) = 0.831866 (all), 0.837336 (pos), 0.824326 (neg) | |
| data reader: epoch = 0, batch = 1271 / 4040 | |
| iter = 1271, cls_loss (cur) = 0.416851, cls_loss (avg) = 0.378422, lr = 0.010000 | |
| iter = 1271, accuracy (cur) = 0.820000 (all), 0.761905 (pos), 0.862069 (neg) | |
| iter = 1271, accuracy (avg) = 0.831747 (all), 0.836582 (pos), 0.824704 (neg) | |
| data reader: epoch = 0, batch = 1272 / 4040 | |
| iter = 1272, cls_loss (cur) = 0.311699, cls_loss (avg) = 0.377754, lr = 0.010000 | |
| iter = 1272, accuracy (cur) = 0.860000 (all), 0.962963 (pos), 0.739130 (neg) | |
| iter = 1272, accuracy (avg) = 0.832029 (all), 0.837846 (pos), 0.823848 (neg) | |
| data reader: epoch = 0, batch = 1273 / 4040 | |
| iter = 1273, cls_loss (cur) = 0.385982, cls_loss (avg) = 0.377837, lr = 0.010000 | |
| iter = 1273, accuracy (cur) = 0.760000 (all), 0.730769 (pos), 0.791667 (neg) | |
| iter = 1273, accuracy (avg) = 0.831309 (all), 0.836775 (pos), 0.823526 (neg) | |
| data reader: epoch = 0, batch = 1274 / 4040 | |
| iter = 1274, cls_loss (cur) = 0.448124, cls_loss (avg) = 0.378540, lr = 0.010000 | |
| iter = 1274, accuracy (cur) = 0.800000 (all), 0.904762 (pos), 0.724138 (neg) | |
| iter = 1274, accuracy (avg) = 0.830996 (all), 0.837455 (pos), 0.822532 (neg) | |
| data reader: epoch = 0, batch = 1275 / 4040 | |
| iter = 1275, cls_loss (cur) = 0.367179, cls_loss (avg) = 0.378426, lr = 0.010000 | |
| iter = 1275, accuracy (cur) = 0.820000 (all), 0.806452 (pos), 0.842105 (neg) | |
| iter = 1275, accuracy (avg) = 0.830886 (all), 0.837145 (pos), 0.822728 (neg) | |
| data reader: epoch = 0, batch = 1276 / 4040 | |
| iter = 1276, cls_loss (cur) = 0.348025, cls_loss (avg) = 0.378122, lr = 0.010000 | |
| iter = 1276, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1276, accuracy (avg) = 0.831177 (all), 0.837523 (pos), 0.822962 (neg) | |
| data reader: epoch = 0, batch = 1277 / 4040 | |
| iter = 1277, cls_loss (cur) = 0.395831, cls_loss (avg) = 0.378299, lr = 0.010000 | |
| iter = 1277, accuracy (cur) = 0.740000 (all), 0.708333 (pos), 0.769231 (neg) | |
| iter = 1277, accuracy (avg) = 0.830266 (all), 0.836232 (pos), 0.822425 (neg) | |
| data reader: epoch = 0, batch = 1278 / 4040 | |
| iter = 1278, cls_loss (cur) = 0.348611, cls_loss (avg) = 0.378002, lr = 0.010000 | |
| iter = 1278, accuracy (cur) = 0.900000 (all), 0.906250 (pos), 0.888889 (neg) | |
| iter = 1278, accuracy (avg) = 0.830963 (all), 0.836932 (pos), 0.823090 (neg) | |
| data reader: epoch = 0, batch = 1279 / 4040 | |
| iter = 1279, cls_loss (cur) = 0.393888, cls_loss (avg) = 0.378161, lr = 0.010000 | |
| iter = 1279, accuracy (cur) = 0.800000 (all), 0.827586 (pos), 0.761905 (neg) | |
| iter = 1279, accuracy (avg) = 0.830653 (all), 0.836838 (pos), 0.822478 (neg) | |
| data reader: epoch = 0, batch = 1280 / 4040 | |
| iter = 1280, cls_loss (cur) = 0.468845, cls_loss (avg) = 0.379068, lr = 0.010000 | |
| iter = 1280, accuracy (cur) = 0.760000 (all), 0.652174 (pos), 0.851852 (neg) | |
| iter = 1280, accuracy (avg) = 0.829947 (all), 0.834992 (pos), 0.822772 (neg) | |
| data reader: epoch = 0, batch = 1281 / 4040 | |
| iter = 1281, cls_loss (cur) = 0.386367, cls_loss (avg) = 0.379141, lr = 0.010000 | |
| iter = 1281, accuracy (cur) = 0.800000 (all), 0.850000 (pos), 0.766667 (neg) | |
| iter = 1281, accuracy (avg) = 0.829647 (all), 0.835142 (pos), 0.822211 (neg) | |
| data reader: epoch = 0, batch = 1282 / 4040 | |
| iter = 1282, cls_loss (cur) = 0.261709, cls_loss (avg) = 0.377966, lr = 0.010000 | |
| iter = 1282, accuracy (cur) = 0.940000 (all), 0.904762 (pos), 0.965517 (neg) | |
| iter = 1282, accuracy (avg) = 0.830751 (all), 0.835838 (pos), 0.823644 (neg) | |
| data reader: epoch = 0, batch = 1283 / 4040 | |
| iter = 1283, cls_loss (cur) = 0.303748, cls_loss (avg) = 0.377224, lr = 0.010000 | |
| iter = 1283, accuracy (cur) = 0.880000 (all), 0.960000 (pos), 0.800000 (neg) | |
| iter = 1283, accuracy (avg) = 0.831243 (all), 0.837080 (pos), 0.823407 (neg) | |
| data reader: epoch = 0, batch = 1284 / 4040 | |
| iter = 1284, cls_loss (cur) = 0.248522, cls_loss (avg) = 0.375937, lr = 0.010000 | |
| iter = 1284, accuracy (cur) = 0.920000 (all), 0.850000 (pos), 0.966667 (neg) | |
| iter = 1284, accuracy (avg) = 0.832131 (all), 0.837209 (pos), 0.824840 (neg) | |
| data reader: epoch = 0, batch = 1285 / 4040 | |
| iter = 1285, cls_loss (cur) = 0.241012, cls_loss (avg) = 0.374588, lr = 0.010000 | |
| iter = 1285, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.892857 (neg) | |
| iter = 1285, accuracy (avg) = 0.833210 (all), 0.838837 (pos), 0.825520 (neg) | |
| data reader: epoch = 0, batch = 1286 / 4040 | |
| iter = 1286, cls_loss (cur) = 0.360506, cls_loss (avg) = 0.374447, lr = 0.010000 | |
| iter = 1286, accuracy (cur) = 0.820000 (all), 0.772727 (pos), 0.857143 (neg) | |
| iter = 1286, accuracy (avg) = 0.833077 (all), 0.838176 (pos), 0.825836 (neg) | |
| data reader: epoch = 0, batch = 1287 / 4040 | |
| iter = 1287, cls_loss (cur) = 0.316659, cls_loss (avg) = 0.373869, lr = 0.010000 | |
| iter = 1287, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 1287, accuracy (avg) = 0.833547 (all), 0.838430 (pos), 0.826506 (neg) | |
| data reader: epoch = 0, batch = 1288 / 4040 | |
| iter = 1288, cls_loss (cur) = 0.534749, cls_loss (avg) = 0.375478, lr = 0.010000 | |
| iter = 1288, accuracy (cur) = 0.740000 (all), 0.772727 (pos), 0.714286 (neg) | |
| iter = 1288, accuracy (avg) = 0.832611 (all), 0.837773 (pos), 0.825384 (neg) | |
| data reader: epoch = 0, batch = 1289 / 4040 | |
| iter = 1289, cls_loss (cur) = 0.376091, cls_loss (avg) = 0.375484, lr = 0.010000 | |
| iter = 1289, accuracy (cur) = 0.800000 (all), 0.826087 (pos), 0.777778 (neg) | |
| iter = 1289, accuracy (avg) = 0.832285 (all), 0.837656 (pos), 0.824908 (neg) | |
| data reader: epoch = 0, batch = 1290 / 4040 | |
| iter = 1290, cls_loss (cur) = 0.466927, cls_loss (avg) = 0.376399, lr = 0.010000 | |
| iter = 1290, accuracy (cur) = 0.820000 (all), 0.680000 (pos), 0.960000 (neg) | |
| iter = 1290, accuracy (avg) = 0.832162 (all), 0.836080 (pos), 0.826259 (neg) | |
| data reader: epoch = 0, batch = 1291 / 4040 | |
| iter = 1291, cls_loss (cur) = 0.403337, cls_loss (avg) = 0.376668, lr = 0.010000 | |
| iter = 1291, accuracy (cur) = 0.820000 (all), 0.730769 (pos), 0.916667 (neg) | |
| iter = 1291, accuracy (avg) = 0.832041 (all), 0.835027 (pos), 0.827163 (neg) | |
| data reader: epoch = 0, batch = 1292 / 4040 | |
| iter = 1292, cls_loss (cur) = 0.361128, cls_loss (avg) = 0.376513, lr = 0.010000 | |
| iter = 1292, accuracy (cur) = 0.820000 (all), 0.774194 (pos), 0.894737 (neg) | |
| iter = 1292, accuracy (avg) = 0.831920 (all), 0.834418 (pos), 0.827839 (neg) | |
| data reader: epoch = 0, batch = 1293 / 4040 | |
| iter = 1293, cls_loss (cur) = 0.263027, cls_loss (avg) = 0.375378, lr = 0.010000 | |
| iter = 1293, accuracy (cur) = 0.900000 (all), 0.863636 (pos), 0.928571 (neg) | |
| iter = 1293, accuracy (avg) = 0.832601 (all), 0.834710 (pos), 0.828846 (neg) | |
| data reader: epoch = 0, batch = 1294 / 4040 | |
| iter = 1294, cls_loss (cur) = 0.420418, cls_loss (avg) = 0.375828, lr = 0.010000 | |
| iter = 1294, accuracy (cur) = 0.740000 (all), 0.800000 (pos), 0.680000 (neg) | |
| iter = 1294, accuracy (avg) = 0.831675 (all), 0.834363 (pos), 0.827358 (neg) | |
| data reader: epoch = 0, batch = 1295 / 4040 | |
| iter = 1295, cls_loss (cur) = 0.323374, cls_loss (avg) = 0.375304, lr = 0.010000 | |
| iter = 1295, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.843750 (neg) | |
| iter = 1295, accuracy (avg) = 0.831958 (all), 0.834909 (pos), 0.827522 (neg) | |
| data reader: epoch = 0, batch = 1296 / 4040 | |
| iter = 1296, cls_loss (cur) = 0.292397, cls_loss (avg) = 0.374475, lr = 0.010000 | |
| iter = 1296, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 1296, accuracy (avg) = 0.832239 (all), 0.835078 (pos), 0.827942 (neg) | |
| data reader: epoch = 0, batch = 1297 / 4040 | |
| iter = 1297, cls_loss (cur) = 0.301987, cls_loss (avg) = 0.373750, lr = 0.010000 | |
| iter = 1297, accuracy (cur) = 0.880000 (all), 0.960000 (pos), 0.800000 (neg) | |
| iter = 1297, accuracy (avg) = 0.832716 (all), 0.836327 (pos), 0.827663 (neg) | |
| data reader: epoch = 0, batch = 1298 / 4040 | |
| iter = 1298, cls_loss (cur) = 0.410072, cls_loss (avg) = 0.374113, lr = 0.010000 | |
| iter = 1298, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.850000 (neg) | |
| iter = 1298, accuracy (avg) = 0.832589 (all), 0.835964 (pos), 0.827886 (neg) | |
| data reader: epoch = 0, batch = 1299 / 4040 | |
| iter = 1299, cls_loss (cur) = 0.393311, cls_loss (avg) = 0.374305, lr = 0.010000 | |
| iter = 1299, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 1299, accuracy (avg) = 0.832663 (all), 0.835521 (pos), 0.828453 (neg) | |
| data reader: epoch = 0, batch = 1300 / 4040 | |
| iter = 1300, cls_loss (cur) = 0.392286, cls_loss (avg) = 0.374485, lr = 0.010000 | |
| iter = 1300, accuracy (cur) = 0.800000 (all), 0.774194 (pos), 0.842105 (neg) | |
| iter = 1300, accuracy (avg) = 0.832337 (all), 0.834908 (pos), 0.828590 (neg) | |
| data reader: epoch = 0, batch = 1301 / 4040 | |
| iter = 1301, cls_loss (cur) = 0.246345, cls_loss (avg) = 0.373203, lr = 0.010000 | |
| iter = 1301, accuracy (cur) = 0.940000 (all), 0.958333 (pos), 0.923077 (neg) | |
| iter = 1301, accuracy (avg) = 0.833413 (all), 0.836142 (pos), 0.829535 (neg) | |
| data reader: epoch = 0, batch = 1302 / 4040 | |
| iter = 1302, cls_loss (cur) = 0.288898, cls_loss (avg) = 0.372360, lr = 0.010000 | |
| iter = 1302, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1302, accuracy (avg) = 0.833679 (all), 0.836531 (pos), 0.829701 (neg) | |
| data reader: epoch = 0, batch = 1303 / 4040 | |
| iter = 1303, cls_loss (cur) = 0.380036, cls_loss (avg) = 0.372437, lr = 0.010000 | |
| iter = 1303, accuracy (cur) = 0.820000 (all), 0.818182 (pos), 0.821429 (neg) | |
| iter = 1303, accuracy (avg) = 0.833542 (all), 0.836347 (pos), 0.829618 (neg) | |
| data reader: epoch = 0, batch = 1304 / 4040 | |
| iter = 1304, cls_loss (cur) = 0.321492, cls_loss (avg) = 0.371928, lr = 0.010000 | |
| iter = 1304, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 1304, accuracy (avg) = 0.833607 (all), 0.835984 (pos), 0.830122 (neg) | |
| data reader: epoch = 0, batch = 1305 / 4040 | |
| iter = 1305, cls_loss (cur) = 0.410512, cls_loss (avg) = 0.372313, lr = 0.010000 | |
| iter = 1305, accuracy (cur) = 0.780000 (all), 0.761905 (pos), 0.793103 (neg) | |
| iter = 1305, accuracy (avg) = 0.833071 (all), 0.835243 (pos), 0.829752 (neg) | |
| data reader: epoch = 0, batch = 1306 / 4040 | |
| iter = 1306, cls_loss (cur) = 0.349482, cls_loss (avg) = 0.372085, lr = 0.010000 | |
| iter = 1306, accuracy (cur) = 0.760000 (all), 0.684211 (pos), 0.806452 (neg) | |
| iter = 1306, accuracy (avg) = 0.832340 (all), 0.833733 (pos), 0.829519 (neg) | |
| data reader: epoch = 0, batch = 1307 / 4040 | |
| iter = 1307, cls_loss (cur) = 0.372289, cls_loss (avg) = 0.372087, lr = 0.010000 | |
| iter = 1307, accuracy (cur) = 0.820000 (all), 0.722222 (pos), 0.875000 (neg) | |
| iter = 1307, accuracy (avg) = 0.832217 (all), 0.832617 (pos), 0.829974 (neg) | |
| data reader: epoch = 0, batch = 1308 / 4040 | |
| iter = 1308, cls_loss (cur) = 0.421366, cls_loss (avg) = 0.372580, lr = 0.010000 | |
| iter = 1308, accuracy (cur) = 0.760000 (all), 0.833333 (pos), 0.718750 (neg) | |
| iter = 1308, accuracy (avg) = 0.831495 (all), 0.832625 (pos), 0.828861 (neg) | |
| data reader: epoch = 0, batch = 1309 / 4040 | |
| iter = 1309, cls_loss (cur) = 0.395507, cls_loss (avg) = 0.372809, lr = 0.010000 | |
| iter = 1309, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 1309, accuracy (avg) = 0.831380 (all), 0.831898 (pos), 0.829373 (neg) | |
| data reader: epoch = 0, batch = 1310 / 4040 | |
| iter = 1310, cls_loss (cur) = 0.301699, cls_loss (avg) = 0.372098, lr = 0.010000 | |
| iter = 1310, accuracy (cur) = 0.880000 (all), 0.807692 (pos), 0.958333 (neg) | |
| iter = 1310, accuracy (avg) = 0.831866 (all), 0.831656 (pos), 0.830662 (neg) | |
| data reader: epoch = 0, batch = 1311 / 4040 | |
| iter = 1311, cls_loss (cur) = 0.235367, cls_loss (avg) = 0.370731, lr = 0.010000 | |
| iter = 1311, accuracy (cur) = 0.940000 (all), 0.920000 (pos), 0.960000 (neg) | |
| iter = 1311, accuracy (avg) = 0.832947 (all), 0.832540 (pos), 0.831956 (neg) | |
| data reader: epoch = 0, batch = 1312 / 4040 | |
| iter = 1312, cls_loss (cur) = 0.354840, cls_loss (avg) = 0.370572, lr = 0.010000 | |
| iter = 1312, accuracy (cur) = 0.760000 (all), 0.653846 (pos), 0.875000 (neg) | |
| iter = 1312, accuracy (avg) = 0.832218 (all), 0.830753 (pos), 0.832386 (neg) | |
| data reader: epoch = 0, batch = 1313 / 4040 | |
| iter = 1313, cls_loss (cur) = 0.266698, cls_loss (avg) = 0.369533, lr = 0.010000 | |
| iter = 1313, accuracy (cur) = 0.940000 (all), 0.933333 (pos), 0.950000 (neg) | |
| iter = 1313, accuracy (avg) = 0.833295 (all), 0.831779 (pos), 0.833562 (neg) | |
| data reader: epoch = 0, batch = 1314 / 4040 | |
| iter = 1314, cls_loss (cur) = 0.484680, cls_loss (avg) = 0.370685, lr = 0.010000 | |
| iter = 1314, accuracy (cur) = 0.720000 (all), 0.681818 (pos), 0.750000 (neg) | |
| iter = 1314, accuracy (avg) = 0.832163 (all), 0.830279 (pos), 0.832727 (neg) | |
| data reader: epoch = 0, batch = 1315 / 4040 | |
| iter = 1315, cls_loss (cur) = 0.429761, cls_loss (avg) = 0.371275, lr = 0.010000 | |
| iter = 1315, accuracy (cur) = 0.780000 (all), 0.666667 (pos), 0.884615 (neg) | |
| iter = 1315, accuracy (avg) = 0.831641 (all), 0.828643 (pos), 0.833246 (neg) | |
| data reader: epoch = 0, batch = 1316 / 4040 | |
| iter = 1316, cls_loss (cur) = 0.276948, cls_loss (avg) = 0.370332, lr = 0.010000 | |
| iter = 1316, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 1316, accuracy (avg) = 0.832324 (all), 0.829587 (pos), 0.833663 (neg) | |
| data reader: epoch = 0, batch = 1317 / 4040 | |
| iter = 1317, cls_loss (cur) = 0.327737, cls_loss (avg) = 0.369906, lr = 0.010000 | |
| iter = 1317, accuracy (cur) = 0.800000 (all), 0.920000 (pos), 0.680000 (neg) | |
| iter = 1317, accuracy (avg) = 0.832001 (all), 0.830491 (pos), 0.832127 (neg) | |
| data reader: epoch = 0, batch = 1318 / 4040 | |
| iter = 1318, cls_loss (cur) = 0.507807, cls_loss (avg) = 0.371285, lr = 0.010000 | |
| iter = 1318, accuracy (cur) = 0.720000 (all), 0.785714 (pos), 0.694444 (neg) | |
| iter = 1318, accuracy (avg) = 0.830881 (all), 0.830044 (pos), 0.830750 (neg) | |
| data reader: epoch = 0, batch = 1319 / 4040 | |
| iter = 1319, cls_loss (cur) = 0.303077, cls_loss (avg) = 0.370603, lr = 0.010000 | |
| iter = 1319, accuracy (cur) = 0.900000 (all), 0.933333 (pos), 0.850000 (neg) | |
| iter = 1319, accuracy (avg) = 0.831572 (all), 0.831076 (pos), 0.830942 (neg) | |
| data reader: epoch = 0, batch = 1320 / 4040 | |
| iter = 1320, cls_loss (cur) = 0.298960, cls_loss (avg) = 0.369887, lr = 0.010000 | |
| iter = 1320, accuracy (cur) = 0.840000 (all), 0.892857 (pos), 0.772727 (neg) | |
| iter = 1320, accuracy (avg) = 0.831657 (all), 0.831694 (pos), 0.830360 (neg) | |
| data reader: epoch = 0, batch = 1321 / 4040 | |
| iter = 1321, cls_loss (cur) = 0.392822, cls_loss (avg) = 0.370116, lr = 0.010000 | |
| iter = 1321, accuracy (cur) = 0.740000 (all), 0.750000 (pos), 0.727273 (neg) | |
| iter = 1321, accuracy (avg) = 0.830740 (all), 0.830877 (pos), 0.829329 (neg) | |
| data reader: epoch = 0, batch = 1322 / 4040 | |
| iter = 1322, cls_loss (cur) = 0.330667, cls_loss (avg) = 0.369722, lr = 0.010000 | |
| iter = 1322, accuracy (cur) = 0.860000 (all), 0.772727 (pos), 0.928571 (neg) | |
| iter = 1322, accuracy (avg) = 0.831033 (all), 0.830296 (pos), 0.830322 (neg) | |
| data reader: epoch = 0, batch = 1323 / 4040 | |
| iter = 1323, cls_loss (cur) = 0.353269, cls_loss (avg) = 0.369557, lr = 0.010000 | |
| iter = 1323, accuracy (cur) = 0.840000 (all), 0.863636 (pos), 0.821429 (neg) | |
| iter = 1323, accuracy (avg) = 0.831122 (all), 0.830629 (pos), 0.830233 (neg) | |
| data reader: epoch = 0, batch = 1324 / 4040 | |
| iter = 1324, cls_loss (cur) = 0.331303, cls_loss (avg) = 0.369174, lr = 0.010000 | |
| iter = 1324, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 1324, accuracy (avg) = 0.831411 (all), 0.830323 (pos), 0.831130 (neg) | |
| data reader: epoch = 0, batch = 1325 / 4040 | |
| iter = 1325, cls_loss (cur) = 0.349387, cls_loss (avg) = 0.368977, lr = 0.010000 | |
| iter = 1325, accuracy (cur) = 0.780000 (all), 0.678571 (pos), 0.909091 (neg) | |
| iter = 1325, accuracy (avg) = 0.830897 (all), 0.828805 (pos), 0.831910 (neg) | |
| data reader: epoch = 0, batch = 1326 / 4040 | |
| iter = 1326, cls_loss (cur) = 0.208995, cls_loss (avg) = 0.367377, lr = 0.010000 | |
| iter = 1326, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.920000 (neg) | |
| iter = 1326, accuracy (avg) = 0.832188 (all), 0.830517 (pos), 0.832791 (neg) | |
| data reader: epoch = 0, batch = 1327 / 4040 | |
| iter = 1327, cls_loss (cur) = 0.304958, cls_loss (avg) = 0.366753, lr = 0.010000 | |
| iter = 1327, accuracy (cur) = 0.820000 (all), 0.766667 (pos), 0.900000 (neg) | |
| iter = 1327, accuracy (avg) = 0.832066 (all), 0.829879 (pos), 0.833463 (neg) | |
| data reader: epoch = 0, batch = 1328 / 4040 | |
| iter = 1328, cls_loss (cur) = 0.489859, cls_loss (avg) = 0.367984, lr = 0.010000 | |
| iter = 1328, accuracy (cur) = 0.800000 (all), 0.678571 (pos), 0.954545 (neg) | |
| iter = 1328, accuracy (avg) = 0.831746 (all), 0.828366 (pos), 0.834674 (neg) | |
| data reader: epoch = 0, batch = 1329 / 4040 | |
| iter = 1329, cls_loss (cur) = 0.514126, cls_loss (avg) = 0.369445, lr = 0.010000 | |
| iter = 1329, accuracy (cur) = 0.680000 (all), 0.687500 (pos), 0.676471 (neg) | |
| iter = 1329, accuracy (avg) = 0.830228 (all), 0.826957 (pos), 0.833092 (neg) | |
| data reader: epoch = 0, batch = 1330 / 4040 | |
| iter = 1330, cls_loss (cur) = 0.195424, cls_loss (avg) = 0.367705, lr = 0.010000 | |
| iter = 1330, accuracy (cur) = 0.960000 (all), 0.933333 (pos), 1.000000 (neg) | |
| iter = 1330, accuracy (avg) = 0.831526 (all), 0.828021 (pos), 0.834761 (neg) | |
| data reader: epoch = 0, batch = 1331 / 4040 | |
| iter = 1331, cls_loss (cur) = 0.497609, cls_loss (avg) = 0.369004, lr = 0.010000 | |
| iter = 1331, accuracy (cur) = 0.740000 (all), 0.807692 (pos), 0.666667 (neg) | |
| iter = 1331, accuracy (avg) = 0.830611 (all), 0.827818 (pos), 0.833080 (neg) | |
| data reader: epoch = 0, batch = 1332 / 4040 | |
| iter = 1332, cls_loss (cur) = 0.319331, cls_loss (avg) = 0.368507, lr = 0.010000 | |
| iter = 1332, accuracy (cur) = 0.840000 (all), 0.916667 (pos), 0.769231 (neg) | |
| iter = 1332, accuracy (avg) = 0.830704 (all), 0.828706 (pos), 0.832441 (neg) | |
| data reader: epoch = 0, batch = 1333 / 4040 | |
| iter = 1333, cls_loss (cur) = 0.450728, cls_loss (avg) = 0.369329, lr = 0.010000 | |
| iter = 1333, accuracy (cur) = 0.760000 (all), 0.850000 (pos), 0.700000 (neg) | |
| iter = 1333, accuracy (avg) = 0.829997 (all), 0.828919 (pos), 0.831117 (neg) | |
| data reader: epoch = 0, batch = 1334 / 4040 | |
| iter = 1334, cls_loss (cur) = 0.312553, cls_loss (avg) = 0.368762, lr = 0.010000 | |
| iter = 1334, accuracy (cur) = 0.860000 (all), 0.958333 (pos), 0.769231 (neg) | |
| iter = 1334, accuracy (avg) = 0.830297 (all), 0.830213 (pos), 0.830498 (neg) | |
| data reader: epoch = 0, batch = 1335 / 4040 | |
| iter = 1335, cls_loss (cur) = 0.543785, cls_loss (avg) = 0.370512, lr = 0.010000 | |
| iter = 1335, accuracy (cur) = 0.700000 (all), 0.652174 (pos), 0.740741 (neg) | |
| iter = 1335, accuracy (avg) = 0.828994 (all), 0.828433 (pos), 0.829601 (neg) | |
| data reader: epoch = 0, batch = 1336 / 4040 | |
| iter = 1336, cls_loss (cur) = 0.385861, cls_loss (avg) = 0.370665, lr = 0.010000 | |
| iter = 1336, accuracy (cur) = 0.760000 (all), 0.681818 (pos), 0.821429 (neg) | |
| iter = 1336, accuracy (avg) = 0.828305 (all), 0.826967 (pos), 0.829519 (neg) | |
| data reader: epoch = 0, batch = 1337 / 4040 | |
| iter = 1337, cls_loss (cur) = 0.433138, cls_loss (avg) = 0.371290, lr = 0.010000 | |
| iter = 1337, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 1337, accuracy (avg) = 0.828421 (all), 0.826614 (pos), 0.830070 (neg) | |
| data reader: epoch = 0, batch = 1338 / 4040 | |
| iter = 1338, cls_loss (cur) = 0.339679, cls_loss (avg) = 0.370974, lr = 0.010000 | |
| iter = 1338, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 1338, accuracy (avg) = 0.828937 (all), 0.826984 (pos), 0.830698 (neg) | |
| data reader: epoch = 0, batch = 1339 / 4040 | |
| iter = 1339, cls_loss (cur) = 0.417656, cls_loss (avg) = 0.371441, lr = 0.010000 | |
| iter = 1339, accuracy (cur) = 0.740000 (all), 0.500000 (pos), 0.928571 (neg) | |
| iter = 1339, accuracy (avg) = 0.828048 (all), 0.823714 (pos), 0.831676 (neg) | |
| data reader: epoch = 0, batch = 1340 / 4040 | |
| iter = 1340, cls_loss (cur) = 0.343194, cls_loss (avg) = 0.371158, lr = 0.010000 | |
| iter = 1340, accuracy (cur) = 0.800000 (all), 0.761905 (pos), 0.827586 (neg) | |
| iter = 1340, accuracy (avg) = 0.827767 (all), 0.823096 (pos), 0.831636 (neg) | |
| data reader: epoch = 0, batch = 1341 / 4040 | |
| iter = 1341, cls_loss (cur) = 0.261525, cls_loss (avg) = 0.370062, lr = 0.010000 | |
| iter = 1341, accuracy (cur) = 0.920000 (all), 0.880000 (pos), 0.960000 (neg) | |
| iter = 1341, accuracy (avg) = 0.828690 (all), 0.823665 (pos), 0.832919 (neg) | |
| data reader: epoch = 0, batch = 1342 / 4040 | |
| iter = 1342, cls_loss (cur) = 0.445034, cls_loss (avg) = 0.370812, lr = 0.010000 | |
| iter = 1342, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 1342, accuracy (avg) = 0.828203 (all), 0.822736 (pos), 0.832923 (neg) | |
| data reader: epoch = 0, batch = 1343 / 4040 | |
| iter = 1343, cls_loss (cur) = 0.365913, cls_loss (avg) = 0.370763, lr = 0.010000 | |
| iter = 1343, accuracy (cur) = 0.800000 (all), 0.652174 (pos), 0.925926 (neg) | |
| iter = 1343, accuracy (avg) = 0.827921 (all), 0.821030 (pos), 0.833853 (neg) | |
| data reader: epoch = 0, batch = 1344 / 4040 | |
| iter = 1344, cls_loss (cur) = 0.367848, cls_loss (avg) = 0.370734, lr = 0.010000 | |
| iter = 1344, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 1344, accuracy (avg) = 0.828042 (all), 0.821220 (pos), 0.833915 (neg) | |
| data reader: epoch = 0, batch = 1345 / 4040 | |
| iter = 1345, cls_loss (cur) = 0.339639, cls_loss (avg) = 0.370423, lr = 0.010000 | |
| iter = 1345, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1345, accuracy (avg) = 0.828161 (all), 0.821758 (pos), 0.833653 (neg) | |
| data reader: epoch = 0, batch = 1346 / 4040 | |
| iter = 1346, cls_loss (cur) = 0.333379, cls_loss (avg) = 0.370052, lr = 0.010000 | |
| iter = 1346, accuracy (cur) = 0.900000 (all), 0.862069 (pos), 0.952381 (neg) | |
| iter = 1346, accuracy (avg) = 0.828880 (all), 0.822161 (pos), 0.834840 (neg) | |
| data reader: epoch = 0, batch = 1347 / 4040 | |
| iter = 1347, cls_loss (cur) = 0.378759, cls_loss (avg) = 0.370139, lr = 0.010000 | |
| iter = 1347, accuracy (cur) = 0.800000 (all), 0.730769 (pos), 0.875000 (neg) | |
| iter = 1347, accuracy (avg) = 0.828591 (all), 0.821247 (pos), 0.835241 (neg) | |
| data reader: epoch = 0, batch = 1348 / 4040 | |
| iter = 1348, cls_loss (cur) = 0.392461, cls_loss (avg) = 0.370362, lr = 0.010000 | |
| iter = 1348, accuracy (cur) = 0.780000 (all), 0.909091 (pos), 0.678571 (neg) | |
| iter = 1348, accuracy (avg) = 0.828105 (all), 0.822126 (pos), 0.833675 (neg) | |
| data reader: epoch = 0, batch = 1349 / 4040 | |
| iter = 1349, cls_loss (cur) = 0.401707, cls_loss (avg) = 0.370676, lr = 0.010000 | |
| iter = 1349, accuracy (cur) = 0.740000 (all), 0.730769 (pos), 0.750000 (neg) | |
| iter = 1349, accuracy (avg) = 0.827224 (all), 0.821212 (pos), 0.832838 (neg) | |
| data reader: epoch = 0, batch = 1350 / 4040 | |
| iter = 1350, cls_loss (cur) = 0.296144, cls_loss (avg) = 0.369931, lr = 0.010000 | |
| iter = 1350, accuracy (cur) = 0.800000 (all), 0.777778 (pos), 0.826087 (neg) | |
| iter = 1350, accuracy (avg) = 0.826952 (all), 0.820778 (pos), 0.832771 (neg) | |
| data reader: epoch = 0, batch = 1351 / 4040 | |
| iter = 1351, cls_loss (cur) = 0.253978, cls_loss (avg) = 0.368771, lr = 0.010000 | |
| iter = 1351, accuracy (cur) = 0.940000 (all), 0.925926 (pos), 0.956522 (neg) | |
| iter = 1351, accuracy (avg) = 0.828082 (all), 0.821829 (pos), 0.834008 (neg) | |
| data reader: epoch = 0, batch = 1352 / 4040 | |
| iter = 1352, cls_loss (cur) = 0.395032, cls_loss (avg) = 0.369034, lr = 0.010000 | |
| iter = 1352, accuracy (cur) = 0.820000 (all), 0.923077 (pos), 0.708333 (neg) | |
| iter = 1352, accuracy (avg) = 0.828001 (all), 0.822842 (pos), 0.832751 (neg) | |
| data reader: epoch = 0, batch = 1353 / 4040 | |
| iter = 1353, cls_loss (cur) = 0.192554, cls_loss (avg) = 0.367269, lr = 0.010000 | |
| iter = 1353, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.923077 (neg) | |
| iter = 1353, accuracy (avg) = 0.829321 (all), 0.824613 (pos), 0.833655 (neg) | |
| data reader: epoch = 0, batch = 1354 / 4040 | |
| iter = 1354, cls_loss (cur) = 0.366761, cls_loss (avg) = 0.367264, lr = 0.010000 | |
| iter = 1354, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.827586 (neg) | |
| iter = 1354, accuracy (avg) = 0.829428 (all), 0.824938 (pos), 0.833594 (neg) | |
| data reader: epoch = 0, batch = 1355 / 4040 | |
| iter = 1355, cls_loss (cur) = 0.339684, cls_loss (avg) = 0.366988, lr = 0.010000 | |
| iter = 1355, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 1355, accuracy (avg) = 0.828934 (all), 0.824467 (pos), 0.833084 (neg) | |
| data reader: epoch = 0, batch = 1356 / 4040 | |
| iter = 1356, cls_loss (cur) = 0.293490, cls_loss (avg) = 0.366253, lr = 0.010000 | |
| iter = 1356, accuracy (cur) = 0.900000 (all), 0.962963 (pos), 0.826087 (neg) | |
| iter = 1356, accuracy (avg) = 0.829644 (all), 0.825852 (pos), 0.833014 (neg) | |
| data reader: epoch = 0, batch = 1357 / 4040 | |
| iter = 1357, cls_loss (cur) = 0.358717, cls_loss (avg) = 0.366178, lr = 0.010000 | |
| iter = 1357, accuracy (cur) = 0.840000 (all), 0.869565 (pos), 0.814815 (neg) | |
| iter = 1357, accuracy (avg) = 0.829748 (all), 0.826289 (pos), 0.832832 (neg) | |
| data reader: epoch = 0, batch = 1358 / 4040 | |
| iter = 1358, cls_loss (cur) = 0.322747, cls_loss (avg) = 0.365743, lr = 0.010000 | |
| iter = 1358, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.862069 (neg) | |
| iter = 1358, accuracy (avg) = 0.830050 (all), 0.826597 (pos), 0.833124 (neg) | |
| data reader: epoch = 0, batch = 1359 / 4040 | |
| iter = 1359, cls_loss (cur) = 0.508322, cls_loss (avg) = 0.367169, lr = 0.010000 | |
| iter = 1359, accuracy (cur) = 0.740000 (all), 0.708333 (pos), 0.769231 (neg) | |
| iter = 1359, accuracy (avg) = 0.829150 (all), 0.825415 (pos), 0.832485 (neg) | |
| data reader: epoch = 0, batch = 1360 / 4040 | |
| iter = 1360, cls_loss (cur) = 0.243986, cls_loss (avg) = 0.365937, lr = 0.010000 | |
| iter = 1360, accuracy (cur) = 0.960000 (all), 0.967742 (pos), 0.947368 (neg) | |
| iter = 1360, accuracy (avg) = 0.830458 (all), 0.826838 (pos), 0.833634 (neg) | |
| data reader: epoch = 0, batch = 1361 / 4040 | |
| iter = 1361, cls_loss (cur) = 0.506033, cls_loss (avg) = 0.367338, lr = 0.010000 | |
| iter = 1361, accuracy (cur) = 0.680000 (all), 0.586207 (pos), 0.809524 (neg) | |
| iter = 1361, accuracy (avg) = 0.828954 (all), 0.824432 (pos), 0.833393 (neg) | |
| data reader: epoch = 0, batch = 1362 / 4040 | |
| iter = 1362, cls_loss (cur) = 0.293746, cls_loss (avg) = 0.366602, lr = 0.010000 | |
| iter = 1362, accuracy (cur) = 0.880000 (all), 0.869565 (pos), 0.888889 (neg) | |
| iter = 1362, accuracy (avg) = 0.829464 (all), 0.824883 (pos), 0.833948 (neg) | |
| data reader: epoch = 0, batch = 1363 / 4040 | |
| iter = 1363, cls_loss (cur) = 0.291412, cls_loss (avg) = 0.365850, lr = 0.010000 | |
| iter = 1363, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1363, accuracy (avg) = 0.829770 (all), 0.825384 (pos), 0.834070 (neg) | |
| data reader: epoch = 0, batch = 1364 / 4040 | |
| iter = 1364, cls_loss (cur) = 0.336917, cls_loss (avg) = 0.365561, lr = 0.010000 | |
| iter = 1364, accuracy (cur) = 0.820000 (all), 0.777778 (pos), 0.843750 (neg) | |
| iter = 1364, accuracy (avg) = 0.829672 (all), 0.824908 (pos), 0.834167 (neg) | |
| data reader: epoch = 0, batch = 1365 / 4040 | |
| iter = 1365, cls_loss (cur) = 0.378915, cls_loss (avg) = 0.365695, lr = 0.010000 | |
| iter = 1365, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 1365, accuracy (avg) = 0.830175 (all), 0.825890 (pos), 0.834159 (neg) | |
| data reader: epoch = 0, batch = 1366 / 4040 | |
| iter = 1366, cls_loss (cur) = 0.320436, cls_loss (avg) = 0.365242, lr = 0.010000 | |
| iter = 1366, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1366, accuracy (avg) = 0.830074 (all), 0.825964 (pos), 0.833894 (neg) | |
| data reader: epoch = 0, batch = 1367 / 4040 | |
| iter = 1367, cls_loss (cur) = 0.338021, cls_loss (avg) = 0.364970, lr = 0.010000 | |
| iter = 1367, accuracy (cur) = 0.840000 (all), 0.818182 (pos), 0.857143 (neg) | |
| iter = 1367, accuracy (avg) = 0.830173 (all), 0.825887 (pos), 0.834126 (neg) | |
| data reader: epoch = 0, batch = 1368 / 4040 | |
| iter = 1368, cls_loss (cur) = 0.430946, cls_loss (avg) = 0.365630, lr = 0.010000 | |
| iter = 1368, accuracy (cur) = 0.780000 (all), 0.739130 (pos), 0.814815 (neg) | |
| iter = 1368, accuracy (avg) = 0.829671 (all), 0.825019 (pos), 0.833933 (neg) | |
| data reader: epoch = 0, batch = 1369 / 4040 | |
| iter = 1369, cls_loss (cur) = 0.313259, cls_loss (avg) = 0.365106, lr = 0.010000 | |
| iter = 1369, accuracy (cur) = 0.880000 (all), 0.947368 (pos), 0.838710 (neg) | |
| iter = 1369, accuracy (avg) = 0.830174 (all), 0.826242 (pos), 0.833981 (neg) | |
| data reader: epoch = 0, batch = 1370 / 4040 | |
| iter = 1370, cls_loss (cur) = 0.226881, cls_loss (avg) = 0.363724, lr = 0.010000 | |
| iter = 1370, accuracy (cur) = 0.960000 (all), 0.909091 (pos), 1.000000 (neg) | |
| iter = 1370, accuracy (avg) = 0.831473 (all), 0.827071 (pos), 0.835641 (neg) | |
| data reader: epoch = 0, batch = 1371 / 4040 | |
| iter = 1371, cls_loss (cur) = 0.373208, cls_loss (avg) = 0.363818, lr = 0.010000 | |
| iter = 1371, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 1371, accuracy (avg) = 0.831558 (all), 0.826731 (pos), 0.836333 (neg) | |
| data reader: epoch = 0, batch = 1372 / 4040 | |
| iter = 1372, cls_loss (cur) = 0.438751, cls_loss (avg) = 0.364568, lr = 0.010000 | |
| iter = 1372, accuracy (cur) = 0.740000 (all), 0.720000 (pos), 0.760000 (neg) | |
| iter = 1372, accuracy (avg) = 0.830642 (all), 0.825664 (pos), 0.835569 (neg) | |
| data reader: epoch = 0, batch = 1373 / 4040 | |
| iter = 1373, cls_loss (cur) = 0.355926, cls_loss (avg) = 0.364481, lr = 0.010000 | |
| iter = 1373, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 1373, accuracy (avg) = 0.830736 (all), 0.825926 (pos), 0.835474 (neg) | |
| data reader: epoch = 0, batch = 1374 / 4040 | |
| iter = 1374, cls_loss (cur) = 0.386931, cls_loss (avg) = 0.364706, lr = 0.010000 | |
| iter = 1374, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.833333 (neg) | |
| iter = 1374, accuracy (avg) = 0.830629 (all), 0.825667 (pos), 0.835453 (neg) | |
| data reader: epoch = 0, batch = 1375 / 4040 | |
| iter = 1375, cls_loss (cur) = 0.372016, cls_loss (avg) = 0.364779, lr = 0.010000 | |
| iter = 1375, accuracy (cur) = 0.840000 (all), 0.782609 (pos), 0.888889 (neg) | |
| iter = 1375, accuracy (avg) = 0.830722 (all), 0.825236 (pos), 0.835987 (neg) | |
| data reader: epoch = 0, batch = 1376 / 4040 | |
| iter = 1376, cls_loss (cur) = 0.427397, cls_loss (avg) = 0.365405, lr = 0.010000 | |
| iter = 1376, accuracy (cur) = 0.760000 (all), 0.727273 (pos), 0.785714 (neg) | |
| iter = 1376, accuracy (avg) = 0.830015 (all), 0.824256 (pos), 0.835485 (neg) | |
| data reader: epoch = 0, batch = 1377 / 4040 | |
| iter = 1377, cls_loss (cur) = 0.462209, cls_loss (avg) = 0.366373, lr = 0.010000 | |
| iter = 1377, accuracy (cur) = 0.800000 (all), 0.806452 (pos), 0.789474 (neg) | |
| iter = 1377, accuracy (avg) = 0.829715 (all), 0.824078 (pos), 0.835024 (neg) | |
| data reader: epoch = 0, batch = 1378 / 4040 | |
| iter = 1378, cls_loss (cur) = 0.329466, cls_loss (avg) = 0.366004, lr = 0.010000 | |
| iter = 1378, accuracy (cur) = 0.880000 (all), 0.852941 (pos), 0.937500 (neg) | |
| iter = 1378, accuracy (avg) = 0.830218 (all), 0.824367 (pos), 0.836049 (neg) | |
| data reader: epoch = 0, batch = 1379 / 4040 | |
| iter = 1379, cls_loss (cur) = 0.439309, cls_loss (avg) = 0.366737, lr = 0.010000 | |
| iter = 1379, accuracy (cur) = 0.820000 (all), 0.851852 (pos), 0.782609 (neg) | |
| iter = 1379, accuracy (avg) = 0.830116 (all), 0.824642 (pos), 0.835515 (neg) | |
| data reader: epoch = 0, batch = 1380 / 4040 | |
| iter = 1380, cls_loss (cur) = 0.373192, cls_loss (avg) = 0.366802, lr = 0.010000 | |
| iter = 1380, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1380, accuracy (avg) = 0.830614 (all), 0.825526 (pos), 0.835678 (neg) | |
| data reader: epoch = 0, batch = 1381 / 4040 | |
| iter = 1381, cls_loss (cur) = 0.430143, cls_loss (avg) = 0.367435, lr = 0.010000 | |
| iter = 1381, accuracy (cur) = 0.760000 (all), 0.629630 (pos), 0.913043 (neg) | |
| iter = 1381, accuracy (avg) = 0.829908 (all), 0.823567 (pos), 0.836452 (neg) | |
| data reader: epoch = 0, batch = 1382 / 4040 | |
| iter = 1382, cls_loss (cur) = 0.363682, cls_loss (avg) = 0.367398, lr = 0.010000 | |
| iter = 1382, accuracy (cur) = 0.840000 (all), 0.913043 (pos), 0.777778 (neg) | |
| iter = 1382, accuracy (avg) = 0.830009 (all), 0.824462 (pos), 0.835865 (neg) | |
| data reader: epoch = 0, batch = 1383 / 4040 | |
| iter = 1383, cls_loss (cur) = 0.393988, cls_loss (avg) = 0.367663, lr = 0.010000 | |
| iter = 1383, accuracy (cur) = 0.800000 (all), 0.950000 (pos), 0.700000 (neg) | |
| iter = 1383, accuracy (avg) = 0.829709 (all), 0.825717 (pos), 0.834506 (neg) | |
| data reader: epoch = 0, batch = 1384 / 4040 | |
| iter = 1384, cls_loss (cur) = 0.303675, cls_loss (avg) = 0.367024, lr = 0.010000 | |
| iter = 1384, accuracy (cur) = 0.900000 (all), 0.913043 (pos), 0.888889 (neg) | |
| iter = 1384, accuracy (avg) = 0.830412 (all), 0.826590 (pos), 0.835050 (neg) | |
| data reader: epoch = 0, batch = 1385 / 4040 | |
| iter = 1385, cls_loss (cur) = 0.350215, cls_loss (avg) = 0.366856, lr = 0.010000 | |
| iter = 1385, accuracy (cur) = 0.880000 (all), 0.800000 (pos), 0.960000 (neg) | |
| iter = 1385, accuracy (avg) = 0.830908 (all), 0.826324 (pos), 0.836300 (neg) | |
| data reader: epoch = 0, batch = 1386 / 4040 | |
| iter = 1386, cls_loss (cur) = 0.322363, cls_loss (avg) = 0.366411, lr = 0.010000 | |
| iter = 1386, accuracy (cur) = 0.840000 (all), 0.969697 (pos), 0.588235 (neg) | |
| iter = 1386, accuracy (avg) = 0.830999 (all), 0.827758 (pos), 0.833819 (neg) | |
| data reader: epoch = 0, batch = 1387 / 4040 | |
| iter = 1387, cls_loss (cur) = 0.377568, cls_loss (avg) = 0.366522, lr = 0.010000 | |
| iter = 1387, accuracy (cur) = 0.800000 (all), 0.916667 (pos), 0.692308 (neg) | |
| iter = 1387, accuracy (avg) = 0.830689 (all), 0.828647 (pos), 0.832404 (neg) | |
| data reader: epoch = 0, batch = 1388 / 4040 | |
| iter = 1388, cls_loss (cur) = 0.362407, cls_loss (avg) = 0.366481, lr = 0.010000 | |
| iter = 1388, accuracy (cur) = 0.800000 (all), 0.821429 (pos), 0.772727 (neg) | |
| iter = 1388, accuracy (avg) = 0.830382 (all), 0.828575 (pos), 0.831807 (neg) | |
| data reader: epoch = 0, batch = 1389 / 4040 | |
| iter = 1389, cls_loss (cur) = 0.300214, cls_loss (avg) = 0.365818, lr = 0.010000 | |
| iter = 1389, accuracy (cur) = 0.880000 (all), 0.925926 (pos), 0.826087 (neg) | |
| iter = 1389, accuracy (avg) = 0.830878 (all), 0.829549 (pos), 0.831750 (neg) | |
| data reader: epoch = 0, batch = 1390 / 4040 | |
| iter = 1390, cls_loss (cur) = 0.430986, cls_loss (avg) = 0.366470, lr = 0.010000 | |
| iter = 1390, accuracy (cur) = 0.720000 (all), 0.741935 (pos), 0.684211 (neg) | |
| iter = 1390, accuracy (avg) = 0.829769 (all), 0.828672 (pos), 0.830275 (neg) | |
| data reader: epoch = 0, batch = 1391 / 4040 | |
| iter = 1391, cls_loss (cur) = 0.468090, cls_loss (avg) = 0.367486, lr = 0.010000 | |
| iter = 1391, accuracy (cur) = 0.800000 (all), 0.904762 (pos), 0.724138 (neg) | |
| iter = 1391, accuracy (avg) = 0.829472 (all), 0.829433 (pos), 0.829213 (neg) | |
| data reader: epoch = 0, batch = 1392 / 4040 | |
| iter = 1392, cls_loss (cur) = 0.349767, cls_loss (avg) = 0.367309, lr = 0.010000 | |
| iter = 1392, accuracy (cur) = 0.880000 (all), 0.894737 (pos), 0.870968 (neg) | |
| iter = 1392, accuracy (avg) = 0.829977 (all), 0.830086 (pos), 0.829631 (neg) | |
| data reader: epoch = 0, batch = 1393 / 4040 | |
| iter = 1393, cls_loss (cur) = 0.297494, cls_loss (avg) = 0.366611, lr = 0.010000 | |
| iter = 1393, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.888889 (neg) | |
| iter = 1393, accuracy (avg) = 0.831077 (all), 0.831785 (pos), 0.830223 (neg) | |
| data reader: epoch = 0, batch = 1394 / 4040 | |
| iter = 1394, cls_loss (cur) = 0.388944, cls_loss (avg) = 0.366834, lr = 0.010000 | |
| iter = 1394, accuracy (cur) = 0.800000 (all), 0.772727 (pos), 0.821429 (neg) | |
| iter = 1394, accuracy (avg) = 0.830766 (all), 0.831195 (pos), 0.830135 (neg) | |
| data reader: epoch = 0, batch = 1395 / 4040 | |
| iter = 1395, cls_loss (cur) = 0.331518, cls_loss (avg) = 0.366481, lr = 0.010000 | |
| iter = 1395, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 1395, accuracy (avg) = 0.830659 (all), 0.830575 (pos), 0.830584 (neg) | |
| data reader: epoch = 0, batch = 1396 / 4040 | |
| iter = 1396, cls_loss (cur) = 0.306307, cls_loss (avg) = 0.365879, lr = 0.010000 | |
| iter = 1396, accuracy (cur) = 0.860000 (all), 0.882353 (pos), 0.812500 (neg) | |
| iter = 1396, accuracy (avg) = 0.830952 (all), 0.831093 (pos), 0.830403 (neg) | |
| data reader: epoch = 0, batch = 1397 / 4040 | |
| iter = 1397, cls_loss (cur) = 0.259712, cls_loss (avg) = 0.364818, lr = 0.010000 | |
| iter = 1397, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.944444 (neg) | |
| iter = 1397, accuracy (avg) = 0.831643 (all), 0.831532 (pos), 0.831544 (neg) | |
| data reader: epoch = 0, batch = 1398 / 4040 | |
| iter = 1398, cls_loss (cur) = 0.326277, cls_loss (avg) = 0.364432, lr = 0.010000 | |
| iter = 1398, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 1398, accuracy (avg) = 0.831726 (all), 0.831550 (pos), 0.831690 (neg) | |
| data reader: epoch = 0, batch = 1399 / 4040 | |
| iter = 1399, cls_loss (cur) = 0.411790, cls_loss (avg) = 0.364906, lr = 0.010000 | |
| iter = 1399, accuracy (cur) = 0.780000 (all), 0.687500 (pos), 0.944444 (neg) | |
| iter = 1399, accuracy (avg) = 0.831209 (all), 0.830110 (pos), 0.832817 (neg) | |
| data reader: epoch = 0, batch = 1400 / 4040 | |
| iter = 1400, cls_loss (cur) = 0.458060, cls_loss (avg) = 0.365837, lr = 0.010000 | |
| iter = 1400, accuracy (cur) = 0.740000 (all), 0.700000 (pos), 0.766667 (neg) | |
| iter = 1400, accuracy (avg) = 0.830297 (all), 0.828808 (pos), 0.832156 (neg) | |
| data reader: epoch = 0, batch = 1401 / 4040 | |
| iter = 1401, cls_loss (cur) = 0.553359, cls_loss (avg) = 0.367713, lr = 0.010000 | |
| iter = 1401, accuracy (cur) = 0.720000 (all), 0.750000 (pos), 0.705882 (neg) | |
| iter = 1401, accuracy (avg) = 0.829194 (all), 0.828020 (pos), 0.830893 (neg) | |
| data reader: epoch = 0, batch = 1402 / 4040 | |
| iter = 1402, cls_loss (cur) = 0.356421, cls_loss (avg) = 0.367600, lr = 0.010000 | |
| iter = 1402, accuracy (cur) = 0.860000 (all), 0.904762 (pos), 0.827586 (neg) | |
| iter = 1402, accuracy (avg) = 0.829502 (all), 0.828788 (pos), 0.830860 (neg) | |
| data reader: epoch = 0, batch = 1403 / 4040 | |
| iter = 1403, cls_loss (cur) = 0.291379, cls_loss (avg) = 0.366837, lr = 0.010000 | |
| iter = 1403, accuracy (cur) = 0.920000 (all), 0.894737 (pos), 0.935484 (neg) | |
| iter = 1403, accuracy (avg) = 0.830407 (all), 0.829447 (pos), 0.831906 (neg) | |
| data reader: epoch = 0, batch = 1404 / 4040 | |
| iter = 1404, cls_loss (cur) = 0.250339, cls_loss (avg) = 0.365672, lr = 0.010000 | |
| iter = 1404, accuracy (cur) = 0.920000 (all), 0.925926 (pos), 0.913043 (neg) | |
| iter = 1404, accuracy (avg) = 0.831303 (all), 0.830412 (pos), 0.832718 (neg) | |
| data reader: epoch = 0, batch = 1405 / 4040 | |
| iter = 1405, cls_loss (cur) = 0.389085, cls_loss (avg) = 0.365907, lr = 0.010000 | |
| iter = 1405, accuracy (cur) = 0.780000 (all), 0.652174 (pos), 0.888889 (neg) | |
| iter = 1405, accuracy (avg) = 0.830790 (all), 0.828630 (pos), 0.833279 (neg) | |
| data reader: epoch = 0, batch = 1406 / 4040 | |
| iter = 1406, cls_loss (cur) = 0.328023, cls_loss (avg) = 0.365528, lr = 0.010000 | |
| iter = 1406, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 1406, accuracy (avg) = 0.831082 (all), 0.829232 (pos), 0.833207 (neg) | |
| data reader: epoch = 0, batch = 1407 / 4040 | |
| iter = 1407, cls_loss (cur) = 0.402994, cls_loss (avg) = 0.365902, lr = 0.010000 | |
| iter = 1407, accuracy (cur) = 0.800000 (all), 0.760000 (pos), 0.840000 (neg) | |
| iter = 1407, accuracy (avg) = 0.830771 (all), 0.828540 (pos), 0.833275 (neg) | |
| data reader: epoch = 0, batch = 1408 / 4040 | |
| iter = 1408, cls_loss (cur) = 0.369891, cls_loss (avg) = 0.365942, lr = 0.010000 | |
| iter = 1408, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 1408, accuracy (avg) = 0.831463 (all), 0.828716 (pos), 0.834526 (neg) | |
| data reader: epoch = 0, batch = 1409 / 4040 | |
| iter = 1409, cls_loss (cur) = 0.312942, cls_loss (avg) = 0.365412, lr = 0.010000 | |
| iter = 1409, accuracy (cur) = 0.840000 (all), 0.818182 (pos), 0.857143 (neg) | |
| iter = 1409, accuracy (avg) = 0.831549 (all), 0.828611 (pos), 0.834752 (neg) | |
| data reader: epoch = 0, batch = 1410 / 4040 | |
| iter = 1410, cls_loss (cur) = 0.266699, cls_loss (avg) = 0.364425, lr = 0.010000 | |
| iter = 1410, accuracy (cur) = 0.880000 (all), 0.962963 (pos), 0.782609 (neg) | |
| iter = 1410, accuracy (avg) = 0.832033 (all), 0.829954 (pos), 0.834231 (neg) | |
| data reader: epoch = 0, batch = 1411 / 4040 | |
| iter = 1411, cls_loss (cur) = 0.438028, cls_loss (avg) = 0.365161, lr = 0.010000 | |
| iter = 1411, accuracy (cur) = 0.780000 (all), 0.727273 (pos), 0.821429 (neg) | |
| iter = 1411, accuracy (avg) = 0.831513 (all), 0.828927 (pos), 0.834103 (neg) | |
| data reader: epoch = 0, batch = 1412 / 4040 | |
| iter = 1412, cls_loss (cur) = 0.263084, cls_loss (avg) = 0.364140, lr = 0.010000 | |
| iter = 1412, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 1412, accuracy (avg) = 0.831998 (all), 0.829100 (pos), 0.834928 (neg) | |
| data reader: epoch = 0, batch = 1413 / 4040 | |
| iter = 1413, cls_loss (cur) = 0.431813, cls_loss (avg) = 0.364817, lr = 0.010000 | |
| iter = 1413, accuracy (cur) = 0.840000 (all), 0.821429 (pos), 0.863636 (neg) | |
| iter = 1413, accuracy (avg) = 0.832078 (all), 0.829023 (pos), 0.835215 (neg) | |
| data reader: epoch = 0, batch = 1414 / 4040 | |
| iter = 1414, cls_loss (cur) = 0.402396, cls_loss (avg) = 0.365193, lr = 0.010000 | |
| iter = 1414, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.714286 (neg) | |
| iter = 1414, accuracy (avg) = 0.831357 (all), 0.828915 (pos), 0.834006 (neg) | |
| data reader: epoch = 0, batch = 1415 / 4040 | |
| iter = 1415, cls_loss (cur) = 0.383055, cls_loss (avg) = 0.365372, lr = 0.010000 | |
| iter = 1415, accuracy (cur) = 0.820000 (all), 0.852941 (pos), 0.750000 (neg) | |
| iter = 1415, accuracy (avg) = 0.831243 (all), 0.829155 (pos), 0.833166 (neg) | |
| data reader: epoch = 0, batch = 1416 / 4040 | |
| iter = 1416, cls_loss (cur) = 0.272300, cls_loss (avg) = 0.364441, lr = 0.010000 | |
| iter = 1416, accuracy (cur) = 0.900000 (all), 0.863636 (pos), 0.928571 (neg) | |
| iter = 1416, accuracy (avg) = 0.831931 (all), 0.829500 (pos), 0.834120 (neg) | |
| data reader: epoch = 0, batch = 1417 / 4040 | |
| iter = 1417, cls_loss (cur) = 0.344470, cls_loss (avg) = 0.364241, lr = 0.010000 | |
| iter = 1417, accuracy (cur) = 0.800000 (all), 0.720000 (pos), 0.880000 (neg) | |
| iter = 1417, accuracy (avg) = 0.831612 (all), 0.828405 (pos), 0.834579 (neg) | |
| data reader: epoch = 0, batch = 1418 / 4040 | |
| iter = 1418, cls_loss (cur) = 0.359753, cls_loss (avg) = 0.364196, lr = 0.010000 | |
| iter = 1418, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1418, accuracy (avg) = 0.831896 (all), 0.828871 (pos), 0.834695 (neg) | |
| data reader: epoch = 0, batch = 1419 / 4040 | |
| iter = 1419, cls_loss (cur) = 0.427496, cls_loss (avg) = 0.364829, lr = 0.010000 | |
| iter = 1419, accuracy (cur) = 0.820000 (all), 0.916667 (pos), 0.730769 (neg) | |
| iter = 1419, accuracy (avg) = 0.831777 (all), 0.829749 (pos), 0.833655 (neg) | |
| data reader: epoch = 0, batch = 1420 / 4040 | |
| iter = 1420, cls_loss (cur) = 0.239110, cls_loss (avg) = 0.363572, lr = 0.010000 | |
| iter = 1420, accuracy (cur) = 0.940000 (all), 0.964286 (pos), 0.909091 (neg) | |
| iter = 1420, accuracy (avg) = 0.832859 (all), 0.831094 (pos), 0.834410 (neg) | |
| data reader: epoch = 0, batch = 1421 / 4040 | |
| iter = 1421, cls_loss (cur) = 0.363498, cls_loss (avg) = 0.363571, lr = 0.010000 | |
| iter = 1421, accuracy (cur) = 0.860000 (all), 0.931034 (pos), 0.761905 (neg) | |
| iter = 1421, accuracy (avg) = 0.833130 (all), 0.832093 (pos), 0.833685 (neg) | |
| data reader: epoch = 0, batch = 1422 / 4040 | |
| iter = 1422, cls_loss (cur) = 0.394538, cls_loss (avg) = 0.363881, lr = 0.010000 | |
| iter = 1422, accuracy (cur) = 0.800000 (all), 0.958333 (pos), 0.653846 (neg) | |
| iter = 1422, accuracy (avg) = 0.832799 (all), 0.833356 (pos), 0.831886 (neg) | |
| data reader: epoch = 0, batch = 1423 / 4040 | |
| iter = 1423, cls_loss (cur) = 0.537003, cls_loss (avg) = 0.365612, lr = 0.010000 | |
| iter = 1423, accuracy (cur) = 0.760000 (all), 0.758621 (pos), 0.761905 (neg) | |
| iter = 1423, accuracy (avg) = 0.832071 (all), 0.832608 (pos), 0.831186 (neg) | |
| data reader: epoch = 0, batch = 1424 / 4040 | |
| iter = 1424, cls_loss (cur) = 0.419400, cls_loss (avg) = 0.366150, lr = 0.010000 | |
| iter = 1424, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1424, accuracy (avg) = 0.832150 (all), 0.833032 (pos), 0.830952 (neg) | |
| data reader: epoch = 0, batch = 1425 / 4040 | |
| iter = 1425, cls_loss (cur) = 0.313428, cls_loss (avg) = 0.365623, lr = 0.010000 | |
| iter = 1425, accuracy (cur) = 0.880000 (all), 0.851852 (pos), 0.913043 (neg) | |
| iter = 1425, accuracy (avg) = 0.832629 (all), 0.833221 (pos), 0.831772 (neg) | |
| data reader: epoch = 0, batch = 1426 / 4040 | |
| iter = 1426, cls_loss (cur) = 0.279936, cls_loss (avg) = 0.364766, lr = 0.010000 | |
| iter = 1426, accuracy (cur) = 0.880000 (all), 0.900000 (pos), 0.866667 (neg) | |
| iter = 1426, accuracy (avg) = 0.833102 (all), 0.833888 (pos), 0.832121 (neg) | |
| data reader: epoch = 0, batch = 1427 / 4040 | |
| iter = 1427, cls_loss (cur) = 0.389211, cls_loss (avg) = 0.365010, lr = 0.010000 | |
| iter = 1427, accuracy (cur) = 0.780000 (all), 0.714286 (pos), 0.827586 (neg) | |
| iter = 1427, accuracy (avg) = 0.832571 (all), 0.832692 (pos), 0.832076 (neg) | |
| data reader: epoch = 0, batch = 1428 / 4040 | |
| iter = 1428, cls_loss (cur) = 0.372719, cls_loss (avg) = 0.365088, lr = 0.010000 | |
| iter = 1428, accuracy (cur) = 0.780000 (all), 0.814815 (pos), 0.739130 (neg) | |
| iter = 1428, accuracy (avg) = 0.832046 (all), 0.832514 (pos), 0.831147 (neg) | |
| data reader: epoch = 0, batch = 1429 / 4040 | |
| iter = 1429, cls_loss (cur) = 0.260103, cls_loss (avg) = 0.364038, lr = 0.010000 | |
| iter = 1429, accuracy (cur) = 0.940000 (all), 0.950000 (pos), 0.933333 (neg) | |
| iter = 1429, accuracy (avg) = 0.833125 (all), 0.833688 (pos), 0.832168 (neg) | |
| data reader: epoch = 0, batch = 1430 / 4040 | |
| iter = 1430, cls_loss (cur) = 0.415844, cls_loss (avg) = 0.364556, lr = 0.010000 | |
| iter = 1430, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 1430, accuracy (avg) = 0.832594 (all), 0.833129 (pos), 0.831673 (neg) | |
| data reader: epoch = 0, batch = 1431 / 4040 | |
| iter = 1431, cls_loss (cur) = 0.429150, cls_loss (avg) = 0.365202, lr = 0.010000 | |
| iter = 1431, accuracy (cur) = 0.740000 (all), 0.730769 (pos), 0.750000 (neg) | |
| iter = 1431, accuracy (avg) = 0.831668 (all), 0.832106 (pos), 0.830856 (neg) | |
| data reader: epoch = 0, batch = 1432 / 4040 | |
| iter = 1432, cls_loss (cur) = 0.343182, cls_loss (avg) = 0.364981, lr = 0.010000 | |
| iter = 1432, accuracy (cur) = 0.840000 (all), 0.681818 (pos), 0.964286 (neg) | |
| iter = 1432, accuracy (avg) = 0.831751 (all), 0.830603 (pos), 0.832190 (neg) | |
| data reader: epoch = 0, batch = 1433 / 4040 | |
| iter = 1433, cls_loss (cur) = 0.242039, cls_loss (avg) = 0.363752, lr = 0.010000 | |
| iter = 1433, accuracy (cur) = 0.880000 (all), 0.750000 (pos), 0.966667 (neg) | |
| iter = 1433, accuracy (avg) = 0.832234 (all), 0.829797 (pos), 0.833535 (neg) | |
| data reader: epoch = 0, batch = 1434 / 4040 | |
| iter = 1434, cls_loss (cur) = 0.418330, cls_loss (avg) = 0.364298, lr = 0.010000 | |
| iter = 1434, accuracy (cur) = 0.760000 (all), 0.652174 (pos), 0.851852 (neg) | |
| iter = 1434, accuracy (avg) = 0.831512 (all), 0.828021 (pos), 0.833718 (neg) | |
| data reader: epoch = 0, batch = 1435 / 4040 | |
| iter = 1435, cls_loss (cur) = 0.320830, cls_loss (avg) = 0.363863, lr = 0.010000 | |
| iter = 1435, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 1435, accuracy (avg) = 0.831796 (all), 0.827889 (pos), 0.834512 (neg) | |
| data reader: epoch = 0, batch = 1436 / 4040 | |
| iter = 1436, cls_loss (cur) = 0.288772, cls_loss (avg) = 0.363112, lr = 0.010000 | |
| iter = 1436, accuracy (cur) = 0.860000 (all), 0.750000 (pos), 0.961538 (neg) | |
| iter = 1436, accuracy (avg) = 0.832078 (all), 0.827110 (pos), 0.835782 (neg) | |
| data reader: epoch = 0, batch = 1437 / 4040 | |
| iter = 1437, cls_loss (cur) = 0.337842, cls_loss (avg) = 0.362860, lr = 0.010000 | |
| iter = 1437, accuracy (cur) = 0.820000 (all), 0.818182 (pos), 0.823529 (neg) | |
| iter = 1437, accuracy (avg) = 0.831958 (all), 0.827020 (pos), 0.835659 (neg) | |
| data reader: epoch = 0, batch = 1438 / 4040 | |
| iter = 1438, cls_loss (cur) = 0.315807, cls_loss (avg) = 0.362389, lr = 0.010000 | |
| iter = 1438, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1438, accuracy (avg) = 0.832238 (all), 0.827550 (pos), 0.835703 (neg) | |
| data reader: epoch = 0, batch = 1439 / 4040 | |
| iter = 1439, cls_loss (cur) = 0.305915, cls_loss (avg) = 0.361824, lr = 0.010000 | |
| iter = 1439, accuracy (cur) = 0.900000 (all), 0.952381 (pos), 0.862069 (neg) | |
| iter = 1439, accuracy (avg) = 0.832916 (all), 0.828798 (pos), 0.835966 (neg) | |
| data reader: epoch = 0, batch = 1440 / 4040 | |
| iter = 1440, cls_loss (cur) = 0.311877, cls_loss (avg) = 0.361325, lr = 0.010000 | |
| iter = 1440, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1440, accuracy (avg) = 0.832787 (all), 0.828844 (pos), 0.835684 (neg) | |
| data reader: epoch = 0, batch = 1441 / 4040 | |
| iter = 1441, cls_loss (cur) = 0.336355, cls_loss (avg) = 0.361075, lr = 0.010000 | |
| iter = 1441, accuracy (cur) = 0.860000 (all), 0.913043 (pos), 0.814815 (neg) | |
| iter = 1441, accuracy (avg) = 0.833059 (all), 0.829686 (pos), 0.835475 (neg) | |
| data reader: epoch = 0, batch = 1442 / 4040 | |
| iter = 1442, cls_loss (cur) = 0.298378, cls_loss (avg) = 0.360448, lr = 0.010000 | |
| iter = 1442, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 1442, accuracy (avg) = 0.833728 (all), 0.830389 (pos), 0.836120 (neg) | |
| data reader: epoch = 0, batch = 1443 / 4040 | |
| iter = 1443, cls_loss (cur) = 0.408324, cls_loss (avg) = 0.360927, lr = 0.010000 | |
| iter = 1443, accuracy (cur) = 0.780000 (all), 0.920000 (pos), 0.640000 (neg) | |
| iter = 1443, accuracy (avg) = 0.833191 (all), 0.831285 (pos), 0.834159 (neg) | |
| data reader: epoch = 0, batch = 1444 / 4040 | |
| iter = 1444, cls_loss (cur) = 0.365296, cls_loss (avg) = 0.360971, lr = 0.010000 | |
| iter = 1444, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.766667 (neg) | |
| iter = 1444, accuracy (avg) = 0.832659 (all), 0.830972 (pos), 0.833484 (neg) | |
| data reader: epoch = 0, batch = 1445 / 4040 | |
| iter = 1445, cls_loss (cur) = 0.300932, cls_loss (avg) = 0.360370, lr = 0.010000 | |
| iter = 1445, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 1445, accuracy (avg) = 0.832932 (all), 0.831862 (pos), 0.833149 (neg) | |
| data reader: epoch = 0, batch = 1446 / 4040 | |
| iter = 1446, cls_loss (cur) = 0.295486, cls_loss (avg) = 0.359721, lr = 0.010000 | |
| iter = 1446, accuracy (cur) = 0.920000 (all), 0.909091 (pos), 0.941176 (neg) | |
| iter = 1446, accuracy (avg) = 0.833803 (all), 0.832635 (pos), 0.834230 (neg) | |
| data reader: epoch = 0, batch = 1447 / 4040 | |
| iter = 1447, cls_loss (cur) = 0.257934, cls_loss (avg) = 0.358703, lr = 0.010000 | |
| iter = 1447, accuracy (cur) = 0.900000 (all), 0.863636 (pos), 0.928571 (neg) | |
| iter = 1447, accuracy (avg) = 0.834465 (all), 0.832945 (pos), 0.835173 (neg) | |
| data reader: epoch = 0, batch = 1448 / 4040 | |
| iter = 1448, cls_loss (cur) = 0.370237, cls_loss (avg) = 0.358819, lr = 0.010000 | |
| iter = 1448, accuracy (cur) = 0.820000 (all), 0.740741 (pos), 0.913043 (neg) | |
| iter = 1448, accuracy (avg) = 0.834320 (all), 0.832023 (pos), 0.835952 (neg) | |
| data reader: epoch = 0, batch = 1449 / 4040 | |
| iter = 1449, cls_loss (cur) = 0.207247, cls_loss (avg) = 0.357303, lr = 0.010000 | |
| iter = 1449, accuracy (cur) = 0.980000 (all), 1.000000 (pos), 0.967742 (neg) | |
| iter = 1449, accuracy (avg) = 0.835777 (all), 0.833703 (pos), 0.837270 (neg) | |
| data reader: epoch = 0, batch = 1450 / 4040 | |
| iter = 1450, cls_loss (cur) = 0.418195, cls_loss (avg) = 0.357912, lr = 0.010000 | |
| iter = 1450, accuracy (cur) = 0.780000 (all), 0.740741 (pos), 0.826087 (neg) | |
| iter = 1450, accuracy (avg) = 0.835219 (all), 0.832773 (pos), 0.837158 (neg) | |
| data reader: epoch = 0, batch = 1451 / 4040 | |
| iter = 1451, cls_loss (cur) = 0.346548, cls_loss (avg) = 0.357798, lr = 0.010000 | |
| iter = 1451, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 1451, accuracy (avg) = 0.835467 (all), 0.832593 (pos), 0.837917 (neg) | |
| data reader: epoch = 0, batch = 1452 / 4040 | |
| iter = 1452, cls_loss (cur) = 0.242169, cls_loss (avg) = 0.356642, lr = 0.010000 | |
| iter = 1452, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.823529 (neg) | |
| iter = 1452, accuracy (avg) = 0.835513 (all), 0.833017 (pos), 0.837773 (neg) | |
| data reader: epoch = 0, batch = 1453 / 4040 | |
| iter = 1453, cls_loss (cur) = 0.424845, cls_loss (avg) = 0.357324, lr = 0.010000 | |
| iter = 1453, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 1453, accuracy (avg) = 0.834957 (all), 0.832465 (pos), 0.837221 (neg) | |
| data reader: epoch = 0, batch = 1454 / 4040 | |
| iter = 1454, cls_loss (cur) = 0.282805, cls_loss (avg) = 0.356579, lr = 0.010000 | |
| iter = 1454, accuracy (cur) = 0.900000 (all), 0.869565 (pos), 0.925926 (neg) | |
| iter = 1454, accuracy (avg) = 0.835608 (all), 0.832836 (pos), 0.838108 (neg) | |
| data reader: epoch = 0, batch = 1455 / 4040 | |
| iter = 1455, cls_loss (cur) = 0.334626, cls_loss (avg) = 0.356359, lr = 0.010000 | |
| iter = 1455, accuracy (cur) = 0.820000 (all), 0.739130 (pos), 0.888889 (neg) | |
| iter = 1455, accuracy (avg) = 0.835452 (all), 0.831899 (pos), 0.838616 (neg) | |
| data reader: epoch = 0, batch = 1456 / 4040 | |
| iter = 1456, cls_loss (cur) = 0.372180, cls_loss (avg) = 0.356518, lr = 0.010000 | |
| iter = 1456, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 1456, accuracy (avg) = 0.835097 (all), 0.831762 (pos), 0.838087 (neg) | |
| data reader: epoch = 0, batch = 1457 / 4040 | |
| iter = 1457, cls_loss (cur) = 0.398808, cls_loss (avg) = 0.356940, lr = 0.010000 | |
| iter = 1457, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.769231 (neg) | |
| iter = 1457, accuracy (avg) = 0.834746 (all), 0.831777 (pos), 0.837398 (neg) | |
| data reader: epoch = 0, batch = 1458 / 4040 | |
| iter = 1458, cls_loss (cur) = 0.412093, cls_loss (avg) = 0.357492, lr = 0.010000 | |
| iter = 1458, accuracy (cur) = 0.740000 (all), 0.730769 (pos), 0.750000 (neg) | |
| iter = 1458, accuracy (avg) = 0.833799 (all), 0.830767 (pos), 0.836524 (neg) | |
| data reader: epoch = 0, batch = 1459 / 4040 | |
| iter = 1459, cls_loss (cur) = 0.414318, cls_loss (avg) = 0.358060, lr = 0.010000 | |
| iter = 1459, accuracy (cur) = 0.780000 (all), 0.758621 (pos), 0.809524 (neg) | |
| iter = 1459, accuracy (avg) = 0.833261 (all), 0.830046 (pos), 0.836254 (neg) | |
| data reader: epoch = 0, batch = 1460 / 4040 | |
| iter = 1460, cls_loss (cur) = 0.256364, cls_loss (avg) = 0.357043, lr = 0.010000 | |
| iter = 1460, accuracy (cur) = 0.860000 (all), 0.928571 (pos), 0.772727 (neg) | |
| iter = 1460, accuracy (avg) = 0.833528 (all), 0.831031 (pos), 0.835619 (neg) | |
| data reader: epoch = 0, batch = 1461 / 4040 | |
| iter = 1461, cls_loss (cur) = 0.429960, cls_loss (avg) = 0.357772, lr = 0.010000 | |
| iter = 1461, accuracy (cur) = 0.760000 (all), 0.769231 (pos), 0.750000 (neg) | |
| iter = 1461, accuracy (avg) = 0.832793 (all), 0.830413 (pos), 0.834763 (neg) | |
| data reader: epoch = 0, batch = 1462 / 4040 | |
| iter = 1462, cls_loss (cur) = 0.352190, cls_loss (avg) = 0.357717, lr = 0.010000 | |
| iter = 1462, accuracy (cur) = 0.760000 (all), 0.750000 (pos), 0.764706 (neg) | |
| iter = 1462, accuracy (avg) = 0.832065 (all), 0.829609 (pos), 0.834062 (neg) | |
| data reader: epoch = 0, batch = 1463 / 4040 | |
| iter = 1463, cls_loss (cur) = 0.368225, cls_loss (avg) = 0.357822, lr = 0.010000 | |
| iter = 1463, accuracy (cur) = 0.840000 (all), 0.931034 (pos), 0.714286 (neg) | |
| iter = 1463, accuracy (avg) = 0.832144 (all), 0.830623 (pos), 0.832865 (neg) | |
| data reader: epoch = 0, batch = 1464 / 4040 | |
| iter = 1464, cls_loss (cur) = 0.476133, cls_loss (avg) = 0.359005, lr = 0.010000 | |
| iter = 1464, accuracy (cur) = 0.780000 (all), 0.884615 (pos), 0.666667 (neg) | |
| iter = 1464, accuracy (avg) = 0.831623 (all), 0.831163 (pos), 0.831203 (neg) | |
| data reader: epoch = 0, batch = 1465 / 4040 | |
| iter = 1465, cls_loss (cur) = 0.291895, cls_loss (avg) = 0.358334, lr = 0.010000 | |
| iter = 1465, accuracy (cur) = 0.860000 (all), 0.826087 (pos), 0.888889 (neg) | |
| iter = 1465, accuracy (avg) = 0.831907 (all), 0.831112 (pos), 0.831779 (neg) | |
| data reader: epoch = 0, batch = 1466 / 4040 | |
| iter = 1466, cls_loss (cur) = 0.506367, cls_loss (avg) = 0.359814, lr = 0.010000 | |
| iter = 1466, accuracy (cur) = 0.720000 (all), 0.814815 (pos), 0.608696 (neg) | |
| iter = 1466, accuracy (avg) = 0.830788 (all), 0.830949 (pos), 0.829549 (neg) | |
| data reader: epoch = 0, batch = 1467 / 4040 | |
| iter = 1467, cls_loss (cur) = 0.408709, cls_loss (avg) = 0.360303, lr = 0.010000 | |
| iter = 1467, accuracy (cur) = 0.800000 (all), 0.782609 (pos), 0.814815 (neg) | |
| iter = 1467, accuracy (avg) = 0.830480 (all), 0.830466 (pos), 0.829401 (neg) | |
| data reader: epoch = 0, batch = 1468 / 4040 | |
| iter = 1468, cls_loss (cur) = 0.323431, cls_loss (avg) = 0.359934, lr = 0.010000 | |
| iter = 1468, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 1468, accuracy (avg) = 0.830575 (all), 0.830161 (pos), 0.829907 (neg) | |
| data reader: epoch = 0, batch = 1469 / 4040 | |
| iter = 1469, cls_loss (cur) = 0.313570, cls_loss (avg) = 0.359471, lr = 0.010000 | |
| iter = 1469, accuracy (cur) = 0.840000 (all), 0.869565 (pos), 0.814815 (neg) | |
| iter = 1469, accuracy (avg) = 0.830669 (all), 0.830555 (pos), 0.829756 (neg) | |
| data reader: epoch = 0, batch = 1470 / 4040 | |
| iter = 1470, cls_loss (cur) = 0.243685, cls_loss (avg) = 0.358313, lr = 0.010000 | |
| iter = 1470, accuracy (cur) = 0.920000 (all), 0.894737 (pos), 0.935484 (neg) | |
| iter = 1470, accuracy (avg) = 0.831562 (all), 0.831197 (pos), 0.830814 (neg) | |
| data reader: epoch = 0, batch = 1471 / 4040 | |
| iter = 1471, cls_loss (cur) = 0.166819, cls_loss (avg) = 0.356398, lr = 0.010000 | |
| iter = 1471, accuracy (cur) = 0.980000 (all), 1.000000 (pos), 0.960000 (neg) | |
| iter = 1471, accuracy (avg) = 0.833047 (all), 0.832885 (pos), 0.832105 (neg) | |
| data reader: epoch = 0, batch = 1472 / 4040 | |
| iter = 1472, cls_loss (cur) = 0.282951, cls_loss (avg) = 0.355663, lr = 0.010000 | |
| iter = 1472, accuracy (cur) = 0.880000 (all), 0.782609 (pos), 0.962963 (neg) | |
| iter = 1472, accuracy (avg) = 0.833516 (all), 0.832383 (pos), 0.833414 (neg) | |
| data reader: epoch = 0, batch = 1473 / 4040 | |
| iter = 1473, cls_loss (cur) = 0.338843, cls_loss (avg) = 0.355495, lr = 0.010000 | |
| iter = 1473, accuracy (cur) = 0.880000 (all), 0.869565 (pos), 0.888889 (neg) | |
| iter = 1473, accuracy (avg) = 0.833981 (all), 0.832754 (pos), 0.833969 (neg) | |
| data reader: epoch = 0, batch = 1474 / 4040 | |
| iter = 1474, cls_loss (cur) = 0.343324, cls_loss (avg) = 0.355374, lr = 0.010000 | |
| iter = 1474, accuracy (cur) = 0.860000 (all), 0.794118 (pos), 1.000000 (neg) | |
| iter = 1474, accuracy (avg) = 0.834241 (all), 0.832368 (pos), 0.835629 (neg) | |
| data reader: epoch = 0, batch = 1475 / 4040 | |
| iter = 1475, cls_loss (cur) = 0.317572, cls_loss (avg) = 0.354995, lr = 0.010000 | |
| iter = 1475, accuracy (cur) = 0.880000 (all), 0.869565 (pos), 0.888889 (neg) | |
| iter = 1475, accuracy (avg) = 0.834699 (all), 0.832740 (pos), 0.836162 (neg) | |
| data reader: epoch = 0, batch = 1476 / 4040 | |
| iter = 1476, cls_loss (cur) = 0.449813, cls_loss (avg) = 0.355944, lr = 0.010000 | |
| iter = 1476, accuracy (cur) = 0.780000 (all), 0.720000 (pos), 0.840000 (neg) | |
| iter = 1476, accuracy (avg) = 0.834152 (all), 0.831613 (pos), 0.836200 (neg) | |
| data reader: epoch = 0, batch = 1477 / 4040 | |
| iter = 1477, cls_loss (cur) = 0.371004, cls_loss (avg) = 0.356094, lr = 0.010000 | |
| iter = 1477, accuracy (cur) = 0.800000 (all), 0.846154 (pos), 0.750000 (neg) | |
| iter = 1477, accuracy (avg) = 0.833810 (all), 0.831758 (pos), 0.835338 (neg) | |
| data reader: epoch = 0, batch = 1478 / 4040 | |
| iter = 1478, cls_loss (cur) = 0.368469, cls_loss (avg) = 0.356218, lr = 0.010000 | |
| iter = 1478, accuracy (cur) = 0.820000 (all), 0.956522 (pos), 0.703704 (neg) | |
| iter = 1478, accuracy (avg) = 0.833672 (all), 0.833006 (pos), 0.834022 (neg) | |
| data reader: epoch = 0, batch = 1479 / 4040 | |
| iter = 1479, cls_loss (cur) = 0.358075, cls_loss (avg) = 0.356237, lr = 0.010000 | |
| iter = 1479, accuracy (cur) = 0.780000 (all), 0.769231 (pos), 0.791667 (neg) | |
| iter = 1479, accuracy (avg) = 0.833136 (all), 0.832368 (pos), 0.833598 (neg) | |
| data reader: epoch = 0, batch = 1480 / 4040 | |
| iter = 1480, cls_loss (cur) = 0.353145, cls_loss (avg) = 0.356206, lr = 0.010000 | |
| iter = 1480, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 1480, accuracy (avg) = 0.833404 (all), 0.832740 (pos), 0.833781 (neg) | |
| data reader: epoch = 0, batch = 1481 / 4040 | |
| iter = 1481, cls_loss (cur) = 0.330374, cls_loss (avg) = 0.355947, lr = 0.010000 | |
| iter = 1481, accuracy (cur) = 0.920000 (all), 0.950000 (pos), 0.900000 (neg) | |
| iter = 1481, accuracy (avg) = 0.834270 (all), 0.833912 (pos), 0.834443 (neg) | |
| data reader: epoch = 0, batch = 1482 / 4040 | |
| iter = 1482, cls_loss (cur) = 0.401537, cls_loss (avg) = 0.356403, lr = 0.010000 | |
| iter = 1482, accuracy (cur) = 0.800000 (all), 0.806452 (pos), 0.789474 (neg) | |
| iter = 1482, accuracy (avg) = 0.833928 (all), 0.833638 (pos), 0.833993 (neg) | |
| data reader: epoch = 0, batch = 1483 / 4040 | |
| iter = 1483, cls_loss (cur) = 0.511397, cls_loss (avg) = 0.357953, lr = 0.010000 | |
| iter = 1483, accuracy (cur) = 0.700000 (all), 0.750000 (pos), 0.636364 (neg) | |
| iter = 1483, accuracy (avg) = 0.832588 (all), 0.832801 (pos), 0.832017 (neg) | |
| data reader: epoch = 0, batch = 1484 / 4040 | |
| iter = 1484, cls_loss (cur) = 0.380703, cls_loss (avg) = 0.358181, lr = 0.010000 | |
| iter = 1484, accuracy (cur) = 0.780000 (all), 0.826087 (pos), 0.740741 (neg) | |
| iter = 1484, accuracy (avg) = 0.832062 (all), 0.832734 (pos), 0.831104 (neg) | |
| data reader: epoch = 0, batch = 1485 / 4040 | |
| iter = 1485, cls_loss (cur) = 0.274930, cls_loss (avg) = 0.357348, lr = 0.010000 | |
| iter = 1485, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 1485, accuracy (avg) = 0.832742 (all), 0.833157 (pos), 0.832024 (neg) | |
| data reader: epoch = 0, batch = 1486 / 4040 | |
| iter = 1486, cls_loss (cur) = 0.390283, cls_loss (avg) = 0.357678, lr = 0.010000 | |
| iter = 1486, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 1486, accuracy (avg) = 0.832614 (all), 0.833287 (pos), 0.831620 (neg) | |
| data reader: epoch = 0, batch = 1487 / 4040 | |
| iter = 1487, cls_loss (cur) = 0.333900, cls_loss (avg) = 0.357440, lr = 0.010000 | |
| iter = 1487, accuracy (cur) = 0.900000 (all), 0.952381 (pos), 0.862069 (neg) | |
| iter = 1487, accuracy (avg) = 0.833288 (all), 0.834478 (pos), 0.831925 (neg) | |
| data reader: epoch = 0, batch = 1488 / 4040 | |
| iter = 1488, cls_loss (cur) = 0.334076, cls_loss (avg) = 0.357206, lr = 0.010000 | |
| iter = 1488, accuracy (cur) = 0.840000 (all), 0.736842 (pos), 0.903226 (neg) | |
| iter = 1488, accuracy (avg) = 0.833355 (all), 0.833502 (pos), 0.832638 (neg) | |
| data reader: epoch = 0, batch = 1489 / 4040 | |
| iter = 1489, cls_loss (cur) = 0.230879, cls_loss (avg) = 0.355943, lr = 0.010000 | |
| iter = 1489, accuracy (cur) = 0.960000 (all), 0.944444 (pos), 0.968750 (neg) | |
| iter = 1489, accuracy (avg) = 0.834622 (all), 0.834611 (pos), 0.833999 (neg) | |
| data reader: epoch = 0, batch = 1490 / 4040 | |
| iter = 1490, cls_loss (cur) = 0.321827, cls_loss (avg) = 0.355602, lr = 0.010000 | |
| iter = 1490, accuracy (cur) = 0.840000 (all), 0.681818 (pos), 0.964286 (neg) | |
| iter = 1490, accuracy (avg) = 0.834676 (all), 0.833083 (pos), 0.835302 (neg) | |
| data reader: epoch = 0, batch = 1491 / 4040 | |
| iter = 1491, cls_loss (cur) = 0.279797, cls_loss (avg) = 0.354844, lr = 0.010000 | |
| iter = 1491, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.875000 (neg) | |
| iter = 1491, accuracy (avg) = 0.835529 (all), 0.834752 (pos), 0.835699 (neg) | |
| data reader: epoch = 0, batch = 1492 / 4040 | |
| iter = 1492, cls_loss (cur) = 0.394836, cls_loss (avg) = 0.355244, lr = 0.010000 | |
| iter = 1492, accuracy (cur) = 0.840000 (all), 0.821429 (pos), 0.863636 (neg) | |
| iter = 1492, accuracy (avg) = 0.835574 (all), 0.834619 (pos), 0.835978 (neg) | |
| data reader: epoch = 0, batch = 1493 / 4040 | |
| iter = 1493, cls_loss (cur) = 0.314358, cls_loss (avg) = 0.354835, lr = 0.010000 | |
| iter = 1493, accuracy (cur) = 0.900000 (all), 0.892857 (pos), 0.909091 (neg) | |
| iter = 1493, accuracy (avg) = 0.836218 (all), 0.835201 (pos), 0.836709 (neg) | |
| data reader: epoch = 0, batch = 1494 / 4040 | |
| iter = 1494, cls_loss (cur) = 0.304601, cls_loss (avg) = 0.354332, lr = 0.010000 | |
| iter = 1494, accuracy (cur) = 0.860000 (all), 0.848485 (pos), 0.882353 (neg) | |
| iter = 1494, accuracy (avg) = 0.836456 (all), 0.835334 (pos), 0.837166 (neg) | |
| data reader: epoch = 0, batch = 1495 / 4040 | |
| iter = 1495, cls_loss (cur) = 0.387800, cls_loss (avg) = 0.354667, lr = 0.010000 | |
| iter = 1495, accuracy (cur) = 0.800000 (all), 0.785714 (pos), 0.818182 (neg) | |
| iter = 1495, accuracy (avg) = 0.836091 (all), 0.834838 (pos), 0.836976 (neg) | |
| data reader: epoch = 0, batch = 1496 / 4040 | |
| iter = 1496, cls_loss (cur) = 0.254426, cls_loss (avg) = 0.353665, lr = 0.010000 | |
| iter = 1496, accuracy (cur) = 0.900000 (all), 0.880000 (pos), 0.920000 (neg) | |
| iter = 1496, accuracy (avg) = 0.836730 (all), 0.835290 (pos), 0.837806 (neg) | |
| data reader: epoch = 0, batch = 1497 / 4040 | |
| iter = 1497, cls_loss (cur) = 0.440262, cls_loss (avg) = 0.354531, lr = 0.010000 | |
| iter = 1497, accuracy (cur) = 0.780000 (all), 0.814815 (pos), 0.739130 (neg) | |
| iter = 1497, accuracy (avg) = 0.836163 (all), 0.835085 (pos), 0.836819 (neg) | |
| data reader: epoch = 0, batch = 1498 / 4040 | |
| iter = 1498, cls_loss (cur) = 0.417406, cls_loss (avg) = 0.355159, lr = 0.010000 | |
| iter = 1498, accuracy (cur) = 0.800000 (all), 0.826087 (pos), 0.777778 (neg) | |
| iter = 1498, accuracy (avg) = 0.835801 (all), 0.834995 (pos), 0.836229 (neg) | |
| data reader: epoch = 0, batch = 1499 / 4040 | |
| iter = 1499, cls_loss (cur) = 0.263086, cls_loss (avg) = 0.354239, lr = 0.010000 | |
| iter = 1499, accuracy (cur) = 0.860000 (all), 0.923077 (pos), 0.791667 (neg) | |
| iter = 1499, accuracy (avg) = 0.836043 (all), 0.835876 (pos), 0.835783 (neg) | |
| data reader: epoch = 0, batch = 1500 / 4040 | |
| iter = 1500, cls_loss (cur) = 0.256537, cls_loss (avg) = 0.353262, lr = 0.010000 | |
| iter = 1500, accuracy (cur) = 0.900000 (all), 0.913043 (pos), 0.888889 (neg) | |
| iter = 1500, accuracy (avg) = 0.836683 (all), 0.836647 (pos), 0.836314 (neg) | |
| data reader: epoch = 0, batch = 1501 / 4040 | |
| iter = 1501, cls_loss (cur) = 0.252603, cls_loss (avg) = 0.352255, lr = 0.010000 | |
| iter = 1501, accuracy (cur) = 0.940000 (all), 0.950000 (pos), 0.933333 (neg) | |
| iter = 1501, accuracy (avg) = 0.837716 (all), 0.837781 (pos), 0.837285 (neg) | |
| data reader: epoch = 0, batch = 1502 / 4040 | |
| iter = 1502, cls_loss (cur) = 0.308453, cls_loss (avg) = 0.351817, lr = 0.010000 | |
| iter = 1502, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 1502, accuracy (avg) = 0.837939 (all), 0.837551 (pos), 0.838042 (neg) | |
| data reader: epoch = 0, batch = 1503 / 4040 | |
| iter = 1503, cls_loss (cur) = 0.303387, cls_loss (avg) = 0.351333, lr = 0.010000 | |
| iter = 1503, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1503, accuracy (avg) = 0.838159 (all), 0.838104 (pos), 0.837844 (neg) | |
| data reader: epoch = 0, batch = 1504 / 4040 | |
| iter = 1504, cls_loss (cur) = 0.343074, cls_loss (avg) = 0.351250, lr = 0.010000 | |
| iter = 1504, accuracy (cur) = 0.860000 (all), 0.863636 (pos), 0.857143 (neg) | |
| iter = 1504, accuracy (avg) = 0.838378 (all), 0.838360 (pos), 0.838037 (neg) | |
| data reader: epoch = 0, batch = 1505 / 4040 | |
| iter = 1505, cls_loss (cur) = 0.356325, cls_loss (avg) = 0.351301, lr = 0.010000 | |
| iter = 1505, accuracy (cur) = 0.860000 (all), 0.848485 (pos), 0.882353 (neg) | |
| iter = 1505, accuracy (avg) = 0.838594 (all), 0.838461 (pos), 0.838480 (neg) | |
| data reader: epoch = 0, batch = 1506 / 4040 | |
| iter = 1506, cls_loss (cur) = 0.457155, cls_loss (avg) = 0.352359, lr = 0.010000 | |
| iter = 1506, accuracy (cur) = 0.780000 (all), 1.000000 (pos), 0.620690 (neg) | |
| iter = 1506, accuracy (avg) = 0.838008 (all), 0.840076 (pos), 0.836302 (neg) | |
| data reader: epoch = 0, batch = 1507 / 4040 | |
| iter = 1507, cls_loss (cur) = 0.269812, cls_loss (avg) = 0.351534, lr = 0.010000 | |
| iter = 1507, accuracy (cur) = 0.920000 (all), 0.904762 (pos), 0.931034 (neg) | |
| iter = 1507, accuracy (avg) = 0.838828 (all), 0.840723 (pos), 0.837249 (neg) | |
| data reader: epoch = 0, batch = 1508 / 4040 | |
| iter = 1508, cls_loss (cur) = 0.409144, cls_loss (avg) = 0.352110, lr = 0.010000 | |
| iter = 1508, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 1508, accuracy (avg) = 0.838240 (all), 0.839624 (pos), 0.837210 (neg) | |
| data reader: epoch = 0, batch = 1509 / 4040 | |
| iter = 1509, cls_loss (cur) = 0.375997, cls_loss (avg) = 0.352349, lr = 0.010000 | |
| iter = 1509, accuracy (cur) = 0.800000 (all), 0.740741 (pos), 0.869565 (neg) | |
| iter = 1509, accuracy (avg) = 0.837857 (all), 0.838635 (pos), 0.837534 (neg) | |
| data reader: epoch = 0, batch = 1510 / 4040 | |
| iter = 1510, cls_loss (cur) = 0.366259, cls_loss (avg) = 0.352488, lr = 0.010000 | |
| iter = 1510, accuracy (cur) = 0.880000 (all), 0.958333 (pos), 0.807692 (neg) | |
| iter = 1510, accuracy (avg) = 0.838279 (all), 0.839832 (pos), 0.837235 (neg) | |
| data reader: epoch = 0, batch = 1511 / 4040 | |
| iter = 1511, cls_loss (cur) = 0.285330, cls_loss (avg) = 0.351816, lr = 0.010000 | |
| iter = 1511, accuracy (cur) = 0.900000 (all), 0.833333 (pos), 1.000000 (neg) | |
| iter = 1511, accuracy (avg) = 0.838896 (all), 0.839767 (pos), 0.838863 (neg) | |
| data reader: epoch = 0, batch = 1512 / 4040 | |
| iter = 1512, cls_loss (cur) = 0.419067, cls_loss (avg) = 0.352489, lr = 0.010000 | |
| iter = 1512, accuracy (cur) = 0.800000 (all), 0.714286 (pos), 0.862069 (neg) | |
| iter = 1512, accuracy (avg) = 0.838507 (all), 0.838512 (pos), 0.839095 (neg) | |
| data reader: epoch = 0, batch = 1513 / 4040 | |
| iter = 1513, cls_loss (cur) = 0.263976, cls_loss (avg) = 0.351604, lr = 0.010000 | |
| iter = 1513, accuracy (cur) = 0.940000 (all), 0.925926 (pos), 0.956522 (neg) | |
| iter = 1513, accuracy (avg) = 0.839522 (all), 0.839386 (pos), 0.840269 (neg) | |
| data reader: epoch = 0, batch = 1514 / 4040 | |
| iter = 1514, cls_loss (cur) = 0.300148, cls_loss (avg) = 0.351089, lr = 0.010000 | |
| iter = 1514, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 1514, accuracy (avg) = 0.839927 (all), 0.839921 (pos), 0.840503 (neg) | |
| data reader: epoch = 0, batch = 1515 / 4040 | |
| iter = 1515, cls_loss (cur) = 0.388243, cls_loss (avg) = 0.351461, lr = 0.010000 | |
| iter = 1515, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 1515, accuracy (avg) = 0.839727 (all), 0.839736 (pos), 0.840280 (neg) | |
| data reader: epoch = 0, batch = 1516 / 4040 | |
| iter = 1516, cls_loss (cur) = 0.381145, cls_loss (avg) = 0.351758, lr = 0.010000 | |
| iter = 1516, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.900000 (neg) | |
| iter = 1516, accuracy (avg) = 0.839730 (all), 0.839338 (pos), 0.840877 (neg) | |
| data reader: epoch = 0, batch = 1517 / 4040 | |
| iter = 1517, cls_loss (cur) = 0.306510, cls_loss (avg) = 0.351305, lr = 0.010000 | |
| iter = 1517, accuracy (cur) = 0.900000 (all), 0.896552 (pos), 0.904762 (neg) | |
| iter = 1517, accuracy (avg) = 0.840333 (all), 0.839911 (pos), 0.841516 (neg) | |
| data reader: epoch = 0, batch = 1518 / 4040 | |
| iter = 1518, cls_loss (cur) = 0.325831, cls_loss (avg) = 0.351050, lr = 0.010000 | |
| iter = 1518, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.857143 (neg) | |
| iter = 1518, accuracy (avg) = 0.840730 (all), 0.840602 (pos), 0.841672 (neg) | |
| data reader: epoch = 0, batch = 1519 / 4040 | |
| iter = 1519, cls_loss (cur) = 0.271966, cls_loss (avg) = 0.350260, lr = 0.010000 | |
| iter = 1519, accuracy (cur) = 0.900000 (all), 0.947368 (pos), 0.870968 (neg) | |
| iter = 1519, accuracy (avg) = 0.841322 (all), 0.841670 (pos), 0.841965 (neg) | |
| data reader: epoch = 0, batch = 1520 / 4040 | |
| iter = 1520, cls_loss (cur) = 0.282220, cls_loss (avg) = 0.349579, lr = 0.010000 | |
| iter = 1520, accuracy (cur) = 0.860000 (all), 0.923077 (pos), 0.791667 (neg) | |
| iter = 1520, accuracy (avg) = 0.841509 (all), 0.842484 (pos), 0.841462 (neg) | |
| data reader: epoch = 0, batch = 1521 / 4040 | |
| iter = 1521, cls_loss (cur) = 0.387399, cls_loss (avg) = 0.349957, lr = 0.010000 | |
| iter = 1521, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1521, accuracy (avg) = 0.841494 (all), 0.842136 (pos), 0.841797 (neg) | |
| data reader: epoch = 0, batch = 1522 / 4040 | |
| iter = 1522, cls_loss (cur) = 0.289907, cls_loss (avg) = 0.349357, lr = 0.010000 | |
| iter = 1522, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 1522, accuracy (avg) = 0.841279 (all), 0.842176 (pos), 0.841296 (neg) | |
| data reader: epoch = 0, batch = 1523 / 4040 | |
| iter = 1523, cls_loss (cur) = 0.285424, cls_loss (avg) = 0.348718, lr = 0.010000 | |
| iter = 1523, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 1523, accuracy (avg) = 0.841866 (all), 0.842505 (pos), 0.842114 (neg) | |
| data reader: epoch = 0, batch = 1524 / 4040 | |
| iter = 1524, cls_loss (cur) = 0.266197, cls_loss (avg) = 0.347892, lr = 0.010000 | |
| iter = 1524, accuracy (cur) = 0.900000 (all), 0.965517 (pos), 0.809524 (neg) | |
| iter = 1524, accuracy (avg) = 0.842448 (all), 0.843735 (pos), 0.841788 (neg) | |
| data reader: epoch = 0, batch = 1525 / 4040 | |
| iter = 1525, cls_loss (cur) = 0.326779, cls_loss (avg) = 0.347681, lr = 0.010000 | |
| iter = 1525, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 1525, accuracy (avg) = 0.842823 (all), 0.844497 (pos), 0.841770 (neg) | |
| data reader: epoch = 0, batch = 1526 / 4040 | |
| iter = 1526, cls_loss (cur) = 0.306898, cls_loss (avg) = 0.347273, lr = 0.010000 | |
| iter = 1526, accuracy (cur) = 0.880000 (all), 0.941176 (pos), 0.848485 (neg) | |
| iter = 1526, accuracy (avg) = 0.843195 (all), 0.845464 (pos), 0.841837 (neg) | |
| data reader: epoch = 0, batch = 1527 / 4040 | |
| iter = 1527, cls_loss (cur) = 0.404339, cls_loss (avg) = 0.347844, lr = 0.010000 | |
| iter = 1527, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1527, accuracy (avg) = 0.843163 (all), 0.845087 (pos), 0.842169 (neg) | |
| data reader: epoch = 0, batch = 1528 / 4040 | |
| iter = 1528, cls_loss (cur) = 0.277915, cls_loss (avg) = 0.347145, lr = 0.010000 | |
| iter = 1528, accuracy (cur) = 0.880000 (all), 0.772727 (pos), 0.964286 (neg) | |
| iter = 1528, accuracy (avg) = 0.843531 (all), 0.844363 (pos), 0.843390 (neg) | |
| data reader: epoch = 0, batch = 1529 / 4040 | |
| iter = 1529, cls_loss (cur) = 0.318989, cls_loss (avg) = 0.346863, lr = 0.010000 | |
| iter = 1529, accuracy (cur) = 0.860000 (all), 0.882353 (pos), 0.848485 (neg) | |
| iter = 1529, accuracy (avg) = 0.843696 (all), 0.844743 (pos), 0.843441 (neg) | |
| data reader: epoch = 0, batch = 1530 / 4040 | |
| iter = 1530, cls_loss (cur) = 0.312297, cls_loss (avg) = 0.346518, lr = 0.010000 | |
| iter = 1530, accuracy (cur) = 0.860000 (all), 0.785714 (pos), 0.954545 (neg) | |
| iter = 1530, accuracy (avg) = 0.843859 (all), 0.844153 (pos), 0.844552 (neg) | |
| data reader: epoch = 0, batch = 1531 / 4040 | |
| iter = 1531, cls_loss (cur) = 0.309522, cls_loss (avg) = 0.346148, lr = 0.010000 | |
| iter = 1531, accuracy (cur) = 0.860000 (all), 0.818182 (pos), 0.892857 (neg) | |
| iter = 1531, accuracy (avg) = 0.844020 (all), 0.843893 (pos), 0.845035 (neg) | |
| data reader: epoch = 0, batch = 1532 / 4040 | |
| iter = 1532, cls_loss (cur) = 0.293576, cls_loss (avg) = 0.345622, lr = 0.010000 | |
| iter = 1532, accuracy (cur) = 0.900000 (all), 0.869565 (pos), 0.925926 (neg) | |
| iter = 1532, accuracy (avg) = 0.844580 (all), 0.844150 (pos), 0.845844 (neg) | |
| data reader: epoch = 0, batch = 1533 / 4040 | |
| iter = 1533, cls_loss (cur) = 0.381473, cls_loss (avg) = 0.345980, lr = 0.010000 | |
| iter = 1533, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 1533, accuracy (avg) = 0.844734 (all), 0.843785 (pos), 0.846552 (neg) | |
| data reader: epoch = 0, batch = 1534 / 4040 | |
| iter = 1534, cls_loss (cur) = 0.373113, cls_loss (avg) = 0.346252, lr = 0.010000 | |
| iter = 1534, accuracy (cur) = 0.760000 (all), 0.857143 (pos), 0.636364 (neg) | |
| iter = 1534, accuracy (avg) = 0.843887 (all), 0.843919 (pos), 0.844450 (neg) | |
| data reader: epoch = 0, batch = 1535 / 4040 | |
| iter = 1535, cls_loss (cur) = 0.461320, cls_loss (avg) = 0.347402, lr = 0.010000 | |
| iter = 1535, accuracy (cur) = 0.720000 (all), 0.650000 (pos), 0.766667 (neg) | |
| iter = 1535, accuracy (avg) = 0.842648 (all), 0.841979 (pos), 0.843672 (neg) | |
| data reader: epoch = 0, batch = 1536 / 4040 | |
| iter = 1536, cls_loss (cur) = 0.209836, cls_loss (avg) = 0.346027, lr = 0.010000 | |
| iter = 1536, accuracy (cur) = 0.940000 (all), 0.960000 (pos), 0.920000 (neg) | |
| iter = 1536, accuracy (avg) = 0.843622 (all), 0.843160 (pos), 0.844436 (neg) | |
| data reader: epoch = 0, batch = 1537 / 4040 | |
| iter = 1537, cls_loss (cur) = 0.275594, cls_loss (avg) = 0.345322, lr = 0.010000 | |
| iter = 1537, accuracy (cur) = 0.960000 (all), 0.904762 (pos), 1.000000 (neg) | |
| iter = 1537, accuracy (avg) = 0.844785 (all), 0.843776 (pos), 0.845991 (neg) | |
| data reader: epoch = 0, batch = 1538 / 4040 | |
| iter = 1538, cls_loss (cur) = 0.369054, cls_loss (avg) = 0.345560, lr = 0.010000 | |
| iter = 1538, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 1538, accuracy (avg) = 0.845138 (all), 0.844227 (pos), 0.846227 (neg) | |
| data reader: epoch = 0, batch = 1539 / 4040 | |
| iter = 1539, cls_loss (cur) = 0.234005, cls_loss (avg) = 0.344444, lr = 0.010000 | |
| iter = 1539, accuracy (cur) = 0.940000 (all), 0.947368 (pos), 0.935484 (neg) | |
| iter = 1539, accuracy (avg) = 0.846086 (all), 0.845258 (pos), 0.847120 (neg) | |
| data reader: epoch = 0, batch = 1540 / 4040 | |
| iter = 1540, cls_loss (cur) = 0.339106, cls_loss (avg) = 0.344391, lr = 0.010000 | |
| iter = 1540, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.863636 (neg) | |
| iter = 1540, accuracy (avg) = 0.846225 (all), 0.845377 (pos), 0.847285 (neg) | |
| data reader: epoch = 0, batch = 1541 / 4040 | |
| iter = 1541, cls_loss (cur) = 0.382391, cls_loss (avg) = 0.344771, lr = 0.010000 | |
| iter = 1541, accuracy (cur) = 0.780000 (all), 0.703704 (pos), 0.869565 (neg) | |
| iter = 1541, accuracy (avg) = 0.845563 (all), 0.843960 (pos), 0.847508 (neg) | |
| data reader: epoch = 0, batch = 1542 / 4040 | |
| iter = 1542, cls_loss (cur) = 0.264722, cls_loss (avg) = 0.343970, lr = 0.010000 | |
| iter = 1542, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.870968 (neg) | |
| iter = 1542, accuracy (avg) = 0.846307 (all), 0.845521 (pos), 0.847742 (neg) | |
| data reader: epoch = 0, batch = 1543 / 4040 | |
| iter = 1543, cls_loss (cur) = 0.314333, cls_loss (avg) = 0.343674, lr = 0.010000 | |
| iter = 1543, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 1543, accuracy (avg) = 0.846244 (all), 0.845912 (pos), 0.847181 (neg) | |
| data reader: epoch = 0, batch = 1544 / 4040 | |
| iter = 1544, cls_loss (cur) = 0.450269, cls_loss (avg) = 0.344740, lr = 0.010000 | |
| iter = 1544, accuracy (cur) = 0.760000 (all), 0.782609 (pos), 0.740741 (neg) | |
| iter = 1544, accuracy (avg) = 0.845382 (all), 0.845279 (pos), 0.846117 (neg) | |
| data reader: epoch = 0, batch = 1545 / 4040 | |
| iter = 1545, cls_loss (cur) = 0.350406, cls_loss (avg) = 0.344797, lr = 0.010000 | |
| iter = 1545, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 1545, accuracy (avg) = 0.845128 (all), 0.844742 (pos), 0.846117 (neg) | |
| data reader: epoch = 0, batch = 1546 / 4040 | |
| iter = 1546, cls_loss (cur) = 0.329170, cls_loss (avg) = 0.344640, lr = 0.010000 | |
| iter = 1546, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 1546, accuracy (avg) = 0.844877 (all), 0.844152 (pos), 0.846293 (neg) | |
| data reader: epoch = 0, batch = 1547 / 4040 | |
| iter = 1547, cls_loss (cur) = 0.224802, cls_loss (avg) = 0.343442, lr = 0.010000 | |
| iter = 1547, accuracy (cur) = 0.940000 (all), 0.931034 (pos), 0.952381 (neg) | |
| iter = 1547, accuracy (avg) = 0.845828 (all), 0.845021 (pos), 0.847353 (neg) | |
| data reader: epoch = 0, batch = 1548 / 4040 | |
| iter = 1548, cls_loss (cur) = 0.367643, cls_loss (avg) = 0.343684, lr = 0.010000 | |
| iter = 1548, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 1548, accuracy (avg) = 0.845770 (all), 0.844971 (pos), 0.847280 (neg) | |
| data reader: epoch = 0, batch = 1549 / 4040 | |
| iter = 1549, cls_loss (cur) = 0.369764, cls_loss (avg) = 0.343945, lr = 0.010000 | |
| iter = 1549, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.863636 (neg) | |
| iter = 1549, accuracy (avg) = 0.845912 (all), 0.845093 (pos), 0.847444 (neg) | |
| data reader: epoch = 0, batch = 1550 / 4040 | |
| iter = 1550, cls_loss (cur) = 0.416156, cls_loss (avg) = 0.344667, lr = 0.010000 | |
| iter = 1550, accuracy (cur) = 0.760000 (all), 0.793103 (pos), 0.714286 (neg) | |
| iter = 1550, accuracy (avg) = 0.845053 (all), 0.844573 (pos), 0.846112 (neg) | |
| data reader: epoch = 0, batch = 1551 / 4040 | |
| iter = 1551, cls_loss (cur) = 0.254894, cls_loss (avg) = 0.343769, lr = 0.010000 | |
| iter = 1551, accuracy (cur) = 0.920000 (all), 0.857143 (pos), 0.965517 (neg) | |
| iter = 1551, accuracy (avg) = 0.845802 (all), 0.844698 (pos), 0.847306 (neg) | |
| data reader: epoch = 0, batch = 1552 / 4040 | |
| iter = 1552, cls_loss (cur) = 0.334154, cls_loss (avg) = 0.343673, lr = 0.010000 | |
| iter = 1552, accuracy (cur) = 0.860000 (all), 0.896552 (pos), 0.809524 (neg) | |
| iter = 1552, accuracy (avg) = 0.845944 (all), 0.845217 (pos), 0.846928 (neg) | |
| data reader: epoch = 0, batch = 1553 / 4040 | |
| iter = 1553, cls_loss (cur) = 0.291988, cls_loss (avg) = 0.343156, lr = 0.010000 | |
| iter = 1553, accuracy (cur) = 0.920000 (all), 0.850000 (pos), 0.966667 (neg) | |
| iter = 1553, accuracy (avg) = 0.846685 (all), 0.845265 (pos), 0.848126 (neg) | |
| data reader: epoch = 0, batch = 1554 / 4040 | |
| iter = 1554, cls_loss (cur) = 0.344979, cls_loss (avg) = 0.343174, lr = 0.010000 | |
| iter = 1554, accuracy (cur) = 0.820000 (all), 0.730769 (pos), 0.916667 (neg) | |
| iter = 1554, accuracy (avg) = 0.846418 (all), 0.844120 (pos), 0.848811 (neg) | |
| data reader: epoch = 0, batch = 1555 / 4040 | |
| iter = 1555, cls_loss (cur) = 0.305861, cls_loss (avg) = 0.342801, lr = 0.010000 | |
| iter = 1555, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.850000 (neg) | |
| iter = 1555, accuracy (avg) = 0.846154 (all), 0.843679 (pos), 0.848823 (neg) | |
| data reader: epoch = 0, batch = 1556 / 4040 | |
| iter = 1556, cls_loss (cur) = 0.287558, cls_loss (avg) = 0.342249, lr = 0.010000 | |
| iter = 1556, accuracy (cur) = 0.880000 (all), 0.878788 (pos), 0.882353 (neg) | |
| iter = 1556, accuracy (avg) = 0.846492 (all), 0.844030 (pos), 0.849158 (neg) | |
| data reader: epoch = 0, batch = 1557 / 4040 | |
| iter = 1557, cls_loss (cur) = 0.401105, cls_loss (avg) = 0.342837, lr = 0.010000 | |
| iter = 1557, accuracy (cur) = 0.720000 (all), 0.720000 (pos), 0.720000 (neg) | |
| iter = 1557, accuracy (avg) = 0.845228 (all), 0.842789 (pos), 0.847867 (neg) | |
| data reader: epoch = 0, batch = 1558 / 4040 | |
| iter = 1558, cls_loss (cur) = 0.210413, cls_loss (avg) = 0.341513, lr = 0.010000 | |
| iter = 1558, accuracy (cur) = 0.920000 (all), 0.961538 (pos), 0.875000 (neg) | |
| iter = 1558, accuracy (avg) = 0.845975 (all), 0.843977 (pos), 0.848138 (neg) | |
| data reader: epoch = 0, batch = 1559 / 4040 | |
| iter = 1559, cls_loss (cur) = 0.275431, cls_loss (avg) = 0.340852, lr = 0.010000 | |
| iter = 1559, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1559, accuracy (avg) = 0.846115 (all), 0.844287 (pos), 0.848118 (neg) | |
| data reader: epoch = 0, batch = 1560 / 4040 | |
| iter = 1560, cls_loss (cur) = 0.576731, cls_loss (avg) = 0.343211, lr = 0.010000 | |
| iter = 1560, accuracy (cur) = 0.680000 (all), 0.882353 (pos), 0.575758 (neg) | |
| iter = 1560, accuracy (avg) = 0.844454 (all), 0.844668 (pos), 0.845394 (neg) | |
| data reader: epoch = 0, batch = 1561 / 4040 | |
| iter = 1561, cls_loss (cur) = 0.346633, cls_loss (avg) = 0.343245, lr = 0.010000 | |
| iter = 1561, accuracy (cur) = 0.820000 (all), 0.851852 (pos), 0.782609 (neg) | |
| iter = 1561, accuracy (avg) = 0.844210 (all), 0.844740 (pos), 0.844767 (neg) | |
| data reader: epoch = 0, batch = 1562 / 4040 | |
| iter = 1562, cls_loss (cur) = 0.448930, cls_loss (avg) = 0.344302, lr = 0.010000 | |
| iter = 1562, accuracy (cur) = 0.820000 (all), 1.000000 (pos), 0.625000 (neg) | |
| iter = 1562, accuracy (avg) = 0.843968 (all), 0.846292 (pos), 0.842569 (neg) | |
| data reader: epoch = 0, batch = 1563 / 4040 | |
| iter = 1563, cls_loss (cur) = 0.356736, cls_loss (avg) = 0.344426, lr = 0.010000 | |
| iter = 1563, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1563, accuracy (avg) = 0.843928 (all), 0.846579 (pos), 0.842220 (neg) | |
| data reader: epoch = 0, batch = 1564 / 4040 | |
| iter = 1564, cls_loss (cur) = 0.316820, cls_loss (avg) = 0.344150, lr = 0.010000 | |
| iter = 1564, accuracy (cur) = 0.880000 (all), 0.878788 (pos), 0.882353 (neg) | |
| iter = 1564, accuracy (avg) = 0.844289 (all), 0.846901 (pos), 0.842621 (neg) | |
| data reader: epoch = 0, batch = 1565 / 4040 | |
| iter = 1565, cls_loss (cur) = 0.334272, cls_loss (avg) = 0.344052, lr = 0.010000 | |
| iter = 1565, accuracy (cur) = 0.820000 (all), 0.807692 (pos), 0.833333 (neg) | |
| iter = 1565, accuracy (avg) = 0.844046 (all), 0.846509 (pos), 0.842529 (neg) | |
| data reader: epoch = 0, batch = 1566 / 4040 | |
| iter = 1566, cls_loss (cur) = 0.368931, cls_loss (avg) = 0.344300, lr = 0.010000 | |
| iter = 1566, accuracy (cur) = 0.800000 (all), 0.923077 (pos), 0.666667 (neg) | |
| iter = 1566, accuracy (avg) = 0.843605 (all), 0.847275 (pos), 0.840770 (neg) | |
| data reader: epoch = 0, batch = 1567 / 4040 | |
| iter = 1567, cls_loss (cur) = 0.345059, cls_loss (avg) = 0.344308, lr = 0.010000 | |
| iter = 1567, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1567, accuracy (avg) = 0.843569 (all), 0.846879 (pos), 0.841112 (neg) | |
| data reader: epoch = 0, batch = 1568 / 4040 | |
| iter = 1568, cls_loss (cur) = 0.345369, cls_loss (avg) = 0.344319, lr = 0.010000 | |
| iter = 1568, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 1568, accuracy (avg) = 0.843534 (all), 0.846410 (pos), 0.841368 (neg) | |
| data reader: epoch = 0, batch = 1569 / 4040 | |
| iter = 1569, cls_loss (cur) = 0.238106, cls_loss (avg) = 0.343256, lr = 0.010000 | |
| iter = 1569, accuracy (cur) = 0.940000 (all), 0.962963 (pos), 0.913043 (neg) | |
| iter = 1569, accuracy (avg) = 0.844498 (all), 0.847576 (pos), 0.842085 (neg) | |
| data reader: epoch = 0, batch = 1570 / 4040 | |
| iter = 1570, cls_loss (cur) = 0.291850, cls_loss (avg) = 0.342742, lr = 0.010000 | |
| iter = 1570, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 1570, accuracy (avg) = 0.844653 (all), 0.847100 (pos), 0.842864 (neg) | |
| data reader: epoch = 0, batch = 1571 / 4040 | |
| iter = 1571, cls_loss (cur) = 0.276577, cls_loss (avg) = 0.342081, lr = 0.010000 | |
| iter = 1571, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 1571, accuracy (avg) = 0.845007 (all), 0.847265 (pos), 0.843364 (neg) | |
| data reader: epoch = 0, batch = 1572 / 4040 | |
| iter = 1572, cls_loss (cur) = 0.427258, cls_loss (avg) = 0.342932, lr = 0.010000 | |
| iter = 1572, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 1572, accuracy (avg) = 0.844557 (all), 0.846975 (pos), 0.842787 (neg) | |
| data reader: epoch = 0, batch = 1573 / 4040 | |
| iter = 1573, cls_loss (cur) = 0.420547, cls_loss (avg) = 0.343709, lr = 0.010000 | |
| iter = 1573, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 1573, accuracy (avg) = 0.844511 (all), 0.847023 (pos), 0.842620 (neg) | |
| data reader: epoch = 0, batch = 1574 / 4040 | |
| iter = 1574, cls_loss (cur) = 0.293608, cls_loss (avg) = 0.343208, lr = 0.010000 | |
| iter = 1574, accuracy (cur) = 0.920000 (all), 0.892857 (pos), 0.954545 (neg) | |
| iter = 1574, accuracy (avg) = 0.845266 (all), 0.847482 (pos), 0.843739 (neg) | |
| data reader: epoch = 0, batch = 1575 / 4040 | |
| iter = 1575, cls_loss (cur) = 0.223027, cls_loss (avg) = 0.342006, lr = 0.010000 | |
| iter = 1575, accuracy (cur) = 0.920000 (all), 0.952381 (pos), 0.896552 (neg) | |
| iter = 1575, accuracy (avg) = 0.846013 (all), 0.848531 (pos), 0.844268 (neg) | |
| data reader: epoch = 0, batch = 1576 / 4040 | |
| iter = 1576, cls_loss (cur) = 0.368238, cls_loss (avg) = 0.342268, lr = 0.010000 | |
| iter = 1576, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 1576, accuracy (avg) = 0.845753 (all), 0.847903 (pos), 0.844461 (neg) | |
| data reader: epoch = 0, batch = 1577 / 4040 | |
| iter = 1577, cls_loss (cur) = 0.199749, cls_loss (avg) = 0.340843, lr = 0.010000 | |
| iter = 1577, accuracy (cur) = 0.960000 (all), 0.956522 (pos), 0.962963 (neg) | |
| iter = 1577, accuracy (avg) = 0.846896 (all), 0.848989 (pos), 0.845646 (neg) | |
| data reader: epoch = 0, batch = 1578 / 4040 | |
| iter = 1578, cls_loss (cur) = 0.256079, cls_loss (avg) = 0.339995, lr = 0.010000 | |
| iter = 1578, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1578, accuracy (avg) = 0.847227 (all), 0.849629 (pos), 0.845708 (neg) | |
| data reader: epoch = 0, batch = 1579 / 4040 | |
| iter = 1579, cls_loss (cur) = 0.454650, cls_loss (avg) = 0.341142, lr = 0.010000 | |
| iter = 1579, accuracy (cur) = 0.740000 (all), 0.793103 (pos), 0.666667 (neg) | |
| iter = 1579, accuracy (avg) = 0.846154 (all), 0.849064 (pos), 0.843918 (neg) | |
| data reader: epoch = 0, batch = 1580 / 4040 | |
| iter = 1580, cls_loss (cur) = 0.351817, cls_loss (avg) = 0.341249, lr = 0.010000 | |
| iter = 1580, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 1580, accuracy (avg) = 0.846093 (all), 0.848973 (pos), 0.843879 (neg) | |
| data reader: epoch = 0, batch = 1581 / 4040 | |
| iter = 1581, cls_loss (cur) = 0.392871, cls_loss (avg) = 0.341765, lr = 0.010000 | |
| iter = 1581, accuracy (cur) = 0.740000 (all), 0.666667 (pos), 0.826087 (neg) | |
| iter = 1581, accuracy (avg) = 0.845032 (all), 0.847150 (pos), 0.843701 (neg) | |
| data reader: epoch = 0, batch = 1582 / 4040 | |
| iter = 1582, cls_loss (cur) = 0.355243, cls_loss (avg) = 0.341900, lr = 0.010000 | |
| iter = 1582, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 1582, accuracy (avg) = 0.845182 (all), 0.846827 (pos), 0.844394 (neg) | |
| data reader: epoch = 0, batch = 1583 / 4040 | |
| iter = 1583, cls_loss (cur) = 0.291830, cls_loss (avg) = 0.341399, lr = 0.010000 | |
| iter = 1583, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 1583, accuracy (avg) = 0.845530 (all), 0.846820 (pos), 0.845117 (neg) | |
| data reader: epoch = 0, batch = 1584 / 4040 | |
| iter = 1584, cls_loss (cur) = 0.308788, cls_loss (avg) = 0.341073, lr = 0.010000 | |
| iter = 1584, accuracy (cur) = 0.900000 (all), 0.818182 (pos), 0.964286 (neg) | |
| iter = 1584, accuracy (avg) = 0.846075 (all), 0.846534 (pos), 0.846309 (neg) | |
| data reader: epoch = 0, batch = 1585 / 4040 | |
| iter = 1585, cls_loss (cur) = 0.274676, cls_loss (avg) = 0.340409, lr = 0.010000 | |
| iter = 1585, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.923077 (neg) | |
| iter = 1585, accuracy (avg) = 0.846414 (all), 0.846402 (pos), 0.847076 (neg) | |
| data reader: epoch = 0, batch = 1586 / 4040 | |
| iter = 1586, cls_loss (cur) = 0.407767, cls_loss (avg) = 0.341082, lr = 0.010000 | |
| iter = 1586, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 1586, accuracy (avg) = 0.845950 (all), 0.846338 (pos), 0.846206 (neg) | |
| data reader: epoch = 0, batch = 1587 / 4040 | |
| iter = 1587, cls_loss (cur) = 0.247394, cls_loss (avg) = 0.340146, lr = 0.010000 | |
| iter = 1587, accuracy (cur) = 0.920000 (all), 0.952381 (pos), 0.896552 (neg) | |
| iter = 1587, accuracy (avg) = 0.846690 (all), 0.847398 (pos), 0.846709 (neg) | |
| data reader: epoch = 0, batch = 1588 / 4040 | |
| iter = 1588, cls_loss (cur) = 0.401027, cls_loss (avg) = 0.340754, lr = 0.010000 | |
| iter = 1588, accuracy (cur) = 0.760000 (all), 0.777778 (pos), 0.739130 (neg) | |
| iter = 1588, accuracy (avg) = 0.845823 (all), 0.846702 (pos), 0.845633 (neg) | |
| data reader: epoch = 0, batch = 1589 / 4040 | |
| iter = 1589, cls_loss (cur) = 0.298702, cls_loss (avg) = 0.340334, lr = 0.010000 | |
| iter = 1589, accuracy (cur) = 0.860000 (all), 0.812500 (pos), 0.944444 (neg) | |
| iter = 1589, accuracy (avg) = 0.845965 (all), 0.846360 (pos), 0.846621 (neg) | |
| data reader: epoch = 0, batch = 1590 / 4040 | |
| iter = 1590, cls_loss (cur) = 0.421404, cls_loss (avg) = 0.341145, lr = 0.010000 | |
| iter = 1590, accuracy (cur) = 0.740000 (all), 0.642857 (pos), 0.863636 (neg) | |
| iter = 1590, accuracy (avg) = 0.844905 (all), 0.844325 (pos), 0.846792 (neg) | |
| data reader: epoch = 0, batch = 1591 / 4040 | |
| iter = 1591, cls_loss (cur) = 0.394775, cls_loss (avg) = 0.341681, lr = 0.010000 | |
| iter = 1591, accuracy (cur) = 0.800000 (all), 0.904762 (pos), 0.724138 (neg) | |
| iter = 1591, accuracy (avg) = 0.844456 (all), 0.844929 (pos), 0.845565 (neg) | |
| data reader: epoch = 0, batch = 1592 / 4040 | |
| iter = 1592, cls_loss (cur) = 0.448269, cls_loss (avg) = 0.342747, lr = 0.010000 | |
| iter = 1592, accuracy (cur) = 0.720000 (all), 0.791667 (pos), 0.653846 (neg) | |
| iter = 1592, accuracy (avg) = 0.843212 (all), 0.844397 (pos), 0.843648 (neg) | |
| data reader: epoch = 0, batch = 1593 / 4040 | |
| iter = 1593, cls_loss (cur) = 0.346751, cls_loss (avg) = 0.342787, lr = 0.010000 | |
| iter = 1593, accuracy (cur) = 0.800000 (all), 0.700000 (pos), 0.950000 (neg) | |
| iter = 1593, accuracy (avg) = 0.842780 (all), 0.842953 (pos), 0.844711 (neg) | |
| data reader: epoch = 0, batch = 1594 / 4040 | |
| iter = 1594, cls_loss (cur) = 0.387340, cls_loss (avg) = 0.343232, lr = 0.010000 | |
| iter = 1594, accuracy (cur) = 0.840000 (all), 0.913043 (pos), 0.777778 (neg) | |
| iter = 1594, accuracy (avg) = 0.842752 (all), 0.843654 (pos), 0.844042 (neg) | |
| data reader: epoch = 0, batch = 1595 / 4040 | |
| iter = 1595, cls_loss (cur) = 0.394979, cls_loss (avg) = 0.343750, lr = 0.010000 | |
| iter = 1595, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 1595, accuracy (avg) = 0.842324 (all), 0.843617 (pos), 0.843202 (neg) | |
| data reader: epoch = 0, batch = 1596 / 4040 | |
| iter = 1596, cls_loss (cur) = 0.501467, cls_loss (avg) = 0.345327, lr = 0.010000 | |
| iter = 1596, accuracy (cur) = 0.720000 (all), 0.838710 (pos), 0.526316 (neg) | |
| iter = 1596, accuracy (avg) = 0.841101 (all), 0.843568 (pos), 0.840033 (neg) | |
| data reader: epoch = 0, batch = 1597 / 4040 | |
| iter = 1597, cls_loss (cur) = 0.346693, cls_loss (avg) = 0.345341, lr = 0.010000 | |
| iter = 1597, accuracy (cur) = 0.880000 (all), 1.000000 (pos), 0.793103 (neg) | |
| iter = 1597, accuracy (avg) = 0.841490 (all), 0.845132 (pos), 0.839563 (neg) | |
| data reader: epoch = 0, batch = 1598 / 4040 | |
| iter = 1598, cls_loss (cur) = 0.336254, cls_loss (avg) = 0.345250, lr = 0.010000 | |
| iter = 1598, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1598, accuracy (avg) = 0.841875 (all), 0.845811 (pos), 0.839686 (neg) | |
| data reader: epoch = 0, batch = 1599 / 4040 | |
| iter = 1599, cls_loss (cur) = 0.293188, cls_loss (avg) = 0.344729, lr = 0.010000 | |
| iter = 1599, accuracy (cur) = 0.820000 (all), 0.793103 (pos), 0.857143 (neg) | |
| iter = 1599, accuracy (avg) = 0.841656 (all), 0.845284 (pos), 0.839861 (neg) | |
| data reader: epoch = 0, batch = 1600 / 4040 | |
| iter = 1600, cls_loss (cur) = 0.449913, cls_loss (avg) = 0.345781, lr = 0.010000 | |
| iter = 1600, accuracy (cur) = 0.760000 (all), 0.760000 (pos), 0.760000 (neg) | |
| iter = 1600, accuracy (avg) = 0.840840 (all), 0.844432 (pos), 0.839062 (neg) | |
| data reader: epoch = 0, batch = 1601 / 4040 | |
| iter = 1601, cls_loss (cur) = 0.282849, cls_loss (avg) = 0.345152, lr = 0.010000 | |
| iter = 1601, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 1601, accuracy (avg) = 0.841431 (all), 0.844449 (pos), 0.840255 (neg) | |
| data reader: epoch = 0, batch = 1602 / 4040 | |
| iter = 1602, cls_loss (cur) = 0.279034, cls_loss (avg) = 0.344490, lr = 0.010000 | |
| iter = 1602, accuracy (cur) = 0.880000 (all), 0.956522 (pos), 0.814815 (neg) | |
| iter = 1602, accuracy (avg) = 0.841817 (all), 0.845570 (pos), 0.840001 (neg) | |
| data reader: epoch = 0, batch = 1603 / 4040 | |
| iter = 1603, cls_loss (cur) = 0.355756, cls_loss (avg) = 0.344603, lr = 0.010000 | |
| iter = 1603, accuracy (cur) = 0.840000 (all), 0.818182 (pos), 0.857143 (neg) | |
| iter = 1603, accuracy (avg) = 0.841799 (all), 0.845296 (pos), 0.840172 (neg) | |
| data reader: epoch = 0, batch = 1604 / 4040 | |
| iter = 1604, cls_loss (cur) = 0.395397, cls_loss (avg) = 0.345111, lr = 0.010000 | |
| iter = 1604, accuracy (cur) = 0.760000 (all), 0.727273 (pos), 0.823529 (neg) | |
| iter = 1604, accuracy (avg) = 0.840981 (all), 0.844115 (pos), 0.840006 (neg) | |
| data reader: epoch = 0, batch = 1605 / 4040 | |
| iter = 1605, cls_loss (cur) = 0.422430, cls_loss (avg) = 0.345884, lr = 0.010000 | |
| iter = 1605, accuracy (cur) = 0.840000 (all), 0.827586 (pos), 0.857143 (neg) | |
| iter = 1605, accuracy (avg) = 0.840971 (all), 0.843950 (pos), 0.840177 (neg) | |
| data reader: epoch = 0, batch = 1606 / 4040 | |
| iter = 1606, cls_loss (cur) = 0.434463, cls_loss (avg) = 0.346770, lr = 0.010000 | |
| iter = 1606, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 1606, accuracy (avg) = 0.840961 (all), 0.843972 (pos), 0.840108 (neg) | |
| data reader: epoch = 0, batch = 1607 / 4040 | |
| iter = 1607, cls_loss (cur) = 0.307304, cls_loss (avg) = 0.346375, lr = 0.010000 | |
| iter = 1607, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 1607, accuracy (avg) = 0.841152 (all), 0.843609 (pos), 0.840874 (neg) | |
| data reader: epoch = 0, batch = 1608 / 4040 | |
| iter = 1608, cls_loss (cur) = 0.349395, cls_loss (avg) = 0.346406, lr = 0.010000 | |
| iter = 1608, accuracy (cur) = 0.880000 (all), 0.950000 (pos), 0.833333 (neg) | |
| iter = 1608, accuracy (avg) = 0.841540 (all), 0.844673 (pos), 0.840799 (neg) | |
| data reader: epoch = 0, batch = 1609 / 4040 | |
| iter = 1609, cls_loss (cur) = 0.383038, cls_loss (avg) = 0.346772, lr = 0.010000 | |
| iter = 1609, accuracy (cur) = 0.820000 (all), 0.827586 (pos), 0.809524 (neg) | |
| iter = 1609, accuracy (avg) = 0.841325 (all), 0.844502 (pos), 0.840486 (neg) | |
| data reader: epoch = 0, batch = 1610 / 4040 | |
| iter = 1610, cls_loss (cur) = 0.357541, cls_loss (avg) = 0.346880, lr = 0.010000 | |
| iter = 1610, accuracy (cur) = 0.840000 (all), 0.838710 (pos), 0.842105 (neg) | |
| iter = 1610, accuracy (avg) = 0.841312 (all), 0.844444 (pos), 0.840502 (neg) | |
| data reader: epoch = 0, batch = 1611 / 4040 | |
| iter = 1611, cls_loss (cur) = 0.385692, cls_loss (avg) = 0.347268, lr = 0.010000 | |
| iter = 1611, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1611, accuracy (avg) = 0.841299 (all), 0.844077 (pos), 0.840847 (neg) | |
| data reader: epoch = 0, batch = 1612 / 4040 | |
| iter = 1612, cls_loss (cur) = 0.214243, cls_loss (avg) = 0.345937, lr = 0.010000 | |
| iter = 1612, accuracy (cur) = 0.920000 (all), 0.892857 (pos), 0.954545 (neg) | |
| iter = 1612, accuracy (avg) = 0.842086 (all), 0.844565 (pos), 0.841984 (neg) | |
| data reader: epoch = 0, batch = 1613 / 4040 | |
| iter = 1613, cls_loss (cur) = 0.313477, cls_loss (avg) = 0.345613, lr = 0.010000 | |
| iter = 1613, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 1613, accuracy (avg) = 0.842465 (all), 0.844380 (pos), 0.842823 (neg) | |
| data reader: epoch = 0, batch = 1614 / 4040 | |
| iter = 1614, cls_loss (cur) = 0.265937, cls_loss (avg) = 0.344816, lr = 0.010000 | |
| iter = 1614, accuracy (cur) = 0.900000 (all), 0.884615 (pos), 0.916667 (neg) | |
| iter = 1614, accuracy (avg) = 0.843040 (all), 0.844782 (pos), 0.843562 (neg) | |
| data reader: epoch = 0, batch = 1615 / 4040 | |
| iter = 1615, cls_loss (cur) = 0.329973, cls_loss (avg) = 0.344668, lr = 0.010000 | |
| iter = 1615, accuracy (cur) = 0.840000 (all), 0.935484 (pos), 0.684211 (neg) | |
| iter = 1615, accuracy (avg) = 0.843010 (all), 0.845689 (pos), 0.841968 (neg) | |
| data reader: epoch = 0, batch = 1616 / 4040 | |
| iter = 1616, cls_loss (cur) = 0.394504, cls_loss (avg) = 0.345166, lr = 0.010000 | |
| iter = 1616, accuracy (cur) = 0.800000 (all), 0.950000 (pos), 0.700000 (neg) | |
| iter = 1616, accuracy (avg) = 0.842580 (all), 0.846732 (pos), 0.840549 (neg) | |
| data reader: epoch = 0, batch = 1617 / 4040 | |
| iter = 1617, cls_loss (cur) = 0.250763, cls_loss (avg) = 0.344222, lr = 0.010000 | |
| iter = 1617, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.818182 (neg) | |
| iter = 1617, accuracy (avg) = 0.842554 (all), 0.846837 (pos), 0.840325 (neg) | |
| data reader: epoch = 0, batch = 1618 / 4040 | |
| iter = 1618, cls_loss (cur) = 0.293980, cls_loss (avg) = 0.343720, lr = 0.010000 | |
| iter = 1618, accuracy (cur) = 0.900000 (all), 0.964286 (pos), 0.818182 (neg) | |
| iter = 1618, accuracy (avg) = 0.843128 (all), 0.848011 (pos), 0.840104 (neg) | |
| data reader: epoch = 0, batch = 1619 / 4040 | |
| iter = 1619, cls_loss (cur) = 0.343002, cls_loss (avg) = 0.343712, lr = 0.010000 | |
| iter = 1619, accuracy (cur) = 0.840000 (all), 0.806452 (pos), 0.894737 (neg) | |
| iter = 1619, accuracy (avg) = 0.843097 (all), 0.847595 (pos), 0.840650 (neg) | |
| data reader: epoch = 0, batch = 1620 / 4040 | |
| iter = 1620, cls_loss (cur) = 0.370779, cls_loss (avg) = 0.343983, lr = 0.010000 | |
| iter = 1620, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1620, accuracy (avg) = 0.843066 (all), 0.847869 (pos), 0.840320 (neg) | |
| data reader: epoch = 0, batch = 1621 / 4040 | |
| iter = 1621, cls_loss (cur) = 0.240508, cls_loss (avg) = 0.342948, lr = 0.010000 | |
| iter = 1621, accuracy (cur) = 0.880000 (all), 0.896552 (pos), 0.857143 (neg) | |
| iter = 1621, accuracy (avg) = 0.843435 (all), 0.848356 (pos), 0.840489 (neg) | |
| data reader: epoch = 0, batch = 1622 / 4040 | |
| iter = 1622, cls_loss (cur) = 0.300506, cls_loss (avg) = 0.342524, lr = 0.010000 | |
| iter = 1622, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 1622, accuracy (avg) = 0.843201 (all), 0.848087 (pos), 0.840266 (neg) | |
| data reader: epoch = 0, batch = 1623 / 4040 | |
| iter = 1623, cls_loss (cur) = 0.345929, cls_loss (avg) = 0.342558, lr = 0.010000 | |
| iter = 1623, accuracy (cur) = 0.820000 (all), 0.925926 (pos), 0.695652 (neg) | |
| iter = 1623, accuracy (avg) = 0.842969 (all), 0.848865 (pos), 0.838819 (neg) | |
| data reader: epoch = 0, batch = 1624 / 4040 | |
| iter = 1624, cls_loss (cur) = 0.199078, cls_loss (avg) = 0.341123, lr = 0.010000 | |
| iter = 1624, accuracy (cur) = 0.940000 (all), 0.920000 (pos), 0.960000 (neg) | |
| iter = 1624, accuracy (avg) = 0.843939 (all), 0.849577 (pos), 0.840031 (neg) | |
| data reader: epoch = 0, batch = 1625 / 4040 | |
| iter = 1625, cls_loss (cur) = 0.345366, cls_loss (avg) = 0.341166, lr = 0.010000 | |
| iter = 1625, accuracy (cur) = 0.800000 (all), 1.000000 (pos), 0.666667 (neg) | |
| iter = 1625, accuracy (avg) = 0.843500 (all), 0.851081 (pos), 0.838298 (neg) | |
| data reader: epoch = 0, batch = 1626 / 4040 | |
| iter = 1626, cls_loss (cur) = 0.408533, cls_loss (avg) = 0.341839, lr = 0.010000 | |
| iter = 1626, accuracy (cur) = 0.780000 (all), 0.840000 (pos), 0.720000 (neg) | |
| iter = 1626, accuracy (avg) = 0.842865 (all), 0.850970 (pos), 0.837115 (neg) | |
| data reader: epoch = 0, batch = 1627 / 4040 | |
| iter = 1627, cls_loss (cur) = 0.308991, cls_loss (avg) = 0.341511, lr = 0.010000 | |
| iter = 1627, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 1627, accuracy (avg) = 0.842836 (all), 0.850979 (pos), 0.837004 (neg) | |
| data reader: epoch = 0, batch = 1628 / 4040 | |
| iter = 1628, cls_loss (cur) = 0.247695, cls_loss (avg) = 0.340573, lr = 0.010000 | |
| iter = 1628, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 1628, accuracy (avg) = 0.843408 (all), 0.851469 (pos), 0.837634 (neg) | |
| data reader: epoch = 0, batch = 1629 / 4040 | |
| iter = 1629, cls_loss (cur) = 0.372883, cls_loss (avg) = 0.340896, lr = 0.010000 | |
| iter = 1629, accuracy (cur) = 0.800000 (all), 0.838710 (pos), 0.736842 (neg) | |
| iter = 1629, accuracy (avg) = 0.842974 (all), 0.851342 (pos), 0.836626 (neg) | |
| data reader: epoch = 0, batch = 1630 / 4040 | |
| iter = 1630, cls_loss (cur) = 0.329099, cls_loss (avg) = 0.340778, lr = 0.010000 | |
| iter = 1630, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 1630, accuracy (avg) = 0.842944 (all), 0.851228 (pos), 0.836660 (neg) | |
| data reader: epoch = 0, batch = 1631 / 4040 | |
| iter = 1631, cls_loss (cur) = 0.272451, cls_loss (avg) = 0.340094, lr = 0.010000 | |
| iter = 1631, accuracy (cur) = 0.900000 (all), 0.880000 (pos), 0.920000 (neg) | |
| iter = 1631, accuracy (avg) = 0.843515 (all), 0.851516 (pos), 0.837493 (neg) | |
| data reader: epoch = 0, batch = 1632 / 4040 | |
| iter = 1632, cls_loss (cur) = 0.367411, cls_loss (avg) = 0.340368, lr = 0.010000 | |
| iter = 1632, accuracy (cur) = 0.800000 (all), 0.680000 (pos), 0.920000 (neg) | |
| iter = 1632, accuracy (avg) = 0.843079 (all), 0.849801 (pos), 0.838319 (neg) | |
| data reader: epoch = 0, batch = 1633 / 4040 | |
| iter = 1633, cls_loss (cur) = 0.385732, cls_loss (avg) = 0.340821, lr = 0.010000 | |
| iter = 1633, accuracy (cur) = 0.760000 (all), 0.821429 (pos), 0.681818 (neg) | |
| iter = 1633, accuracy (avg) = 0.842249 (all), 0.849517 (pos), 0.836754 (neg) | |
| data reader: epoch = 0, batch = 1634 / 4040 | |
| iter = 1634, cls_loss (cur) = 0.353512, cls_loss (avg) = 0.340948, lr = 0.010000 | |
| iter = 1634, accuracy (cur) = 0.820000 (all), 0.904762 (pos), 0.758621 (neg) | |
| iter = 1634, accuracy (avg) = 0.842026 (all), 0.850069 (pos), 0.835972 (neg) | |
| data reader: epoch = 0, batch = 1635 / 4040 | |
| iter = 1635, cls_loss (cur) = 0.352475, cls_loss (avg) = 0.341063, lr = 0.010000 | |
| iter = 1635, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 1635, accuracy (avg) = 0.842406 (all), 0.849751 (pos), 0.836898 (neg) | |
| data reader: epoch = 0, batch = 1636 / 4040 | |
| iter = 1636, cls_loss (cur) = 0.191281, cls_loss (avg) = 0.339566, lr = 0.010000 | |
| iter = 1636, accuracy (cur) = 0.940000 (all), 0.961538 (pos), 0.916667 (neg) | |
| iter = 1636, accuracy (avg) = 0.843382 (all), 0.850868 (pos), 0.837696 (neg) | |
| data reader: epoch = 0, batch = 1637 / 4040 | |
| iter = 1637, cls_loss (cur) = 0.217508, cls_loss (avg) = 0.338345, lr = 0.010000 | |
| iter = 1637, accuracy (cur) = 0.940000 (all), 0.964286 (pos), 0.909091 (neg) | |
| iter = 1637, accuracy (avg) = 0.844348 (all), 0.852003 (pos), 0.838410 (neg) | |
| data reader: epoch = 0, batch = 1638 / 4040 | |
| iter = 1638, cls_loss (cur) = 0.370632, cls_loss (avg) = 0.338668, lr = 0.010000 | |
| iter = 1638, accuracy (cur) = 0.840000 (all), 0.827586 (pos), 0.857143 (neg) | |
| iter = 1638, accuracy (avg) = 0.844305 (all), 0.851759 (pos), 0.838597 (neg) | |
| data reader: epoch = 0, batch = 1639 / 4040 | |
| iter = 1639, cls_loss (cur) = 0.235791, cls_loss (avg) = 0.337639, lr = 0.010000 | |
| iter = 1639, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.880000 (neg) | |
| iter = 1639, accuracy (avg) = 0.845262 (all), 0.853241 (pos), 0.839011 (neg) | |
| data reader: epoch = 0, batch = 1640 / 4040 | |
| iter = 1640, cls_loss (cur) = 0.384564, cls_loss (avg) = 0.338108, lr = 0.010000 | |
| iter = 1640, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1640, accuracy (avg) = 0.845209 (all), 0.853459 (pos), 0.838698 (neg) | |
| data reader: epoch = 0, batch = 1641 / 4040 | |
| iter = 1641, cls_loss (cur) = 0.353846, cls_loss (avg) = 0.338266, lr = 0.010000 | |
| iter = 1641, accuracy (cur) = 0.760000 (all), 0.720000 (pos), 0.800000 (neg) | |
| iter = 1641, accuracy (avg) = 0.844357 (all), 0.852124 (pos), 0.838311 (neg) | |
| data reader: epoch = 0, batch = 1642 / 4040 | |
| iter = 1642, cls_loss (cur) = 0.243249, cls_loss (avg) = 0.337316, lr = 0.010000 | |
| iter = 1642, accuracy (cur) = 0.920000 (all), 0.875000 (pos), 0.961538 (neg) | |
| iter = 1642, accuracy (avg) = 0.845113 (all), 0.852353 (pos), 0.839543 (neg) | |
| data reader: epoch = 0, batch = 1643 / 4040 | |
| iter = 1643, cls_loss (cur) = 0.320088, cls_loss (avg) = 0.337143, lr = 0.010000 | |
| iter = 1643, accuracy (cur) = 0.880000 (all), 0.961538 (pos), 0.791667 (neg) | |
| iter = 1643, accuracy (avg) = 0.845462 (all), 0.853445 (pos), 0.839065 (neg) | |
| data reader: epoch = 0, batch = 1644 / 4040 | |
| iter = 1644, cls_loss (cur) = 0.315479, cls_loss (avg) = 0.336927, lr = 0.010000 | |
| iter = 1644, accuracy (cur) = 0.820000 (all), 0.666667 (pos), 0.961538 (neg) | |
| iter = 1644, accuracy (avg) = 0.845208 (all), 0.851577 (pos), 0.840289 (neg) | |
| data reader: epoch = 0, batch = 1645 / 4040 | |
| iter = 1645, cls_loss (cur) = 0.241988, cls_loss (avg) = 0.335977, lr = 0.010000 | |
| iter = 1645, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 1645, accuracy (avg) = 0.845755 (all), 0.852292 (pos), 0.840636 (neg) | |
| data reader: epoch = 0, batch = 1646 / 4040 | |
| iter = 1646, cls_loss (cur) = 0.288445, cls_loss (avg) = 0.335502, lr = 0.010000 | |
| iter = 1646, accuracy (cur) = 0.880000 (all), 0.939394 (pos), 0.764706 (neg) | |
| iter = 1646, accuracy (avg) = 0.846098 (all), 0.853163 (pos), 0.839877 (neg) | |
| data reader: epoch = 0, batch = 1647 / 4040 | |
| iter = 1647, cls_loss (cur) = 0.316594, cls_loss (avg) = 0.335313, lr = 0.010000 | |
| iter = 1647, accuracy (cur) = 0.800000 (all), 0.840000 (pos), 0.760000 (neg) | |
| iter = 1647, accuracy (avg) = 0.845637 (all), 0.853031 (pos), 0.839078 (neg) | |
| data reader: epoch = 0, batch = 1648 / 4040 | |
| iter = 1648, cls_loss (cur) = 0.252516, cls_loss (avg) = 0.334485, lr = 0.010000 | |
| iter = 1648, accuracy (cur) = 0.900000 (all), 0.931034 (pos), 0.857143 (neg) | |
| iter = 1648, accuracy (avg) = 0.846181 (all), 0.853811 (pos), 0.839259 (neg) | |
| data reader: epoch = 0, batch = 1649 / 4040 | |
| iter = 1649, cls_loss (cur) = 0.273505, cls_loss (avg) = 0.333875, lr = 0.010000 | |
| iter = 1649, accuracy (cur) = 0.880000 (all), 0.958333 (pos), 0.807692 (neg) | |
| iter = 1649, accuracy (avg) = 0.846519 (all), 0.854856 (pos), 0.838943 (neg) | |
| data reader: epoch = 0, batch = 1650 / 4040 | |
| iter = 1650, cls_loss (cur) = 0.398860, cls_loss (avg) = 0.334525, lr = 0.010000 | |
| iter = 1650, accuracy (cur) = 0.840000 (all), 1.000000 (pos), 0.733333 (neg) | |
| iter = 1650, accuracy (avg) = 0.846454 (all), 0.856308 (pos), 0.837887 (neg) | |
| data reader: epoch = 0, batch = 1651 / 4040 | |
| iter = 1651, cls_loss (cur) = 0.335811, cls_loss (avg) = 0.334538, lr = 0.010000 | |
| iter = 1651, accuracy (cur) = 0.820000 (all), 0.961538 (pos), 0.666667 (neg) | |
| iter = 1651, accuracy (avg) = 0.846189 (all), 0.857360 (pos), 0.836175 (neg) | |
| data reader: epoch = 0, batch = 1652 / 4040 | |
| iter = 1652, cls_loss (cur) = 0.487325, cls_loss (avg) = 0.336066, lr = 0.010000 | |
| iter = 1652, accuracy (cur) = 0.720000 (all), 0.814815 (pos), 0.608696 (neg) | |
| iter = 1652, accuracy (avg) = 0.844927 (all), 0.856935 (pos), 0.833900 (neg) | |
| data reader: epoch = 0, batch = 1653 / 4040 | |
| iter = 1653, cls_loss (cur) = 0.392747, cls_loss (avg) = 0.336633, lr = 0.010000 | |
| iter = 1653, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.846154 (neg) | |
| iter = 1653, accuracy (avg) = 0.844478 (all), 0.855865 (pos), 0.834023 (neg) | |
| data reader: epoch = 0, batch = 1654 / 4040 | |
| iter = 1654, cls_loss (cur) = 0.301646, cls_loss (avg) = 0.336283, lr = 0.010000 | |
| iter = 1654, accuracy (cur) = 0.880000 (all), 1.000000 (pos), 0.750000 (neg) | |
| iter = 1654, accuracy (avg) = 0.844833 (all), 0.857307 (pos), 0.833182 (neg) | |
| data reader: epoch = 0, batch = 1655 / 4040 | |
| iter = 1655, cls_loss (cur) = 0.395396, cls_loss (avg) = 0.336874, lr = 0.010000 | |
| iter = 1655, accuracy (cur) = 0.800000 (all), 0.791667 (pos), 0.807692 (neg) | |
| iter = 1655, accuracy (avg) = 0.844385 (all), 0.856650 (pos), 0.832928 (neg) | |
| data reader: epoch = 0, batch = 1656 / 4040 | |
| iter = 1656, cls_loss (cur) = 0.448669, cls_loss (avg) = 0.337992, lr = 0.010000 | |
| iter = 1656, accuracy (cur) = 0.780000 (all), 0.625000 (pos), 0.923077 (neg) | |
| iter = 1656, accuracy (avg) = 0.843741 (all), 0.854334 (pos), 0.833829 (neg) | |
| data reader: epoch = 0, batch = 1657 / 4040 | |
| iter = 1657, cls_loss (cur) = 0.296746, cls_loss (avg) = 0.337579, lr = 0.010000 | |
| iter = 1657, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 1657, accuracy (avg) = 0.844103 (all), 0.854719 (pos), 0.834127 (neg) | |
| data reader: epoch = 0, batch = 1658 / 4040 | |
| iter = 1658, cls_loss (cur) = 0.331435, cls_loss (avg) = 0.337518, lr = 0.010000 | |
| iter = 1658, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.931034 (neg) | |
| iter = 1658, accuracy (avg) = 0.844662 (all), 0.854743 (pos), 0.835096 (neg) | |
| data reader: epoch = 0, batch = 1659 / 4040 | |
| iter = 1659, cls_loss (cur) = 0.347799, cls_loss (avg) = 0.337621, lr = 0.010000 | |
| iter = 1659, accuracy (cur) = 0.880000 (all), 0.800000 (pos), 0.960000 (neg) | |
| iter = 1659, accuracy (avg) = 0.845016 (all), 0.854196 (pos), 0.836345 (neg) | |
| data reader: epoch = 0, batch = 1660 / 4040 | |
| iter = 1660, cls_loss (cur) = 0.377274, cls_loss (avg) = 0.338017, lr = 0.010000 | |
| iter = 1660, accuracy (cur) = 0.840000 (all), 0.925926 (pos), 0.739130 (neg) | |
| iter = 1660, accuracy (avg) = 0.844966 (all), 0.854913 (pos), 0.835373 (neg) | |
| data reader: epoch = 0, batch = 1661 / 4040 | |
| iter = 1661, cls_loss (cur) = 0.245133, cls_loss (avg) = 0.337088, lr = 0.010000 | |
| iter = 1661, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.954545 (neg) | |
| iter = 1661, accuracy (avg) = 0.845516 (all), 0.854935 (pos), 0.836565 (neg) | |
| data reader: epoch = 0, batch = 1662 / 4040 | |
| iter = 1662, cls_loss (cur) = 0.434822, cls_loss (avg) = 0.338066, lr = 0.010000 | |
| iter = 1662, accuracy (cur) = 0.840000 (all), 0.736842 (pos), 0.903226 (neg) | |
| iter = 1662, accuracy (avg) = 0.845461 (all), 0.853755 (pos), 0.837231 (neg) | |
| data reader: epoch = 0, batch = 1663 / 4040 | |
| iter = 1663, cls_loss (cur) = 0.321448, cls_loss (avg) = 0.337900, lr = 0.010000 | |
| iter = 1663, accuracy (cur) = 0.820000 (all), 0.772727 (pos), 0.857143 (neg) | |
| iter = 1663, accuracy (avg) = 0.845206 (all), 0.852944 (pos), 0.837431 (neg) | |
| data reader: epoch = 0, batch = 1664 / 4040 | |
| iter = 1664, cls_loss (cur) = 0.306771, cls_loss (avg) = 0.337588, lr = 0.010000 | |
| iter = 1664, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 1664, accuracy (avg) = 0.845554 (all), 0.852597 (pos), 0.838342 (neg) | |
| data reader: epoch = 0, batch = 1665 / 4040 | |
| iter = 1665, cls_loss (cur) = 0.329563, cls_loss (avg) = 0.337508, lr = 0.010000 | |
| iter = 1665, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 1665, accuracy (avg) = 0.845699 (all), 0.852532 (pos), 0.838709 (neg) | |
| data reader: epoch = 0, batch = 1666 / 4040 | |
| iter = 1666, cls_loss (cur) = 0.316846, cls_loss (avg) = 0.337301, lr = 0.010000 | |
| iter = 1666, accuracy (cur) = 0.860000 (all), 0.950000 (pos), 0.800000 (neg) | |
| iter = 1666, accuracy (avg) = 0.845842 (all), 0.853507 (pos), 0.838321 (neg) | |
| data reader: epoch = 0, batch = 1667 / 4040 | |
| iter = 1667, cls_loss (cur) = 0.324693, cls_loss (avg) = 0.337175, lr = 0.010000 | |
| iter = 1667, accuracy (cur) = 0.840000 (all), 0.866667 (pos), 0.800000 (neg) | |
| iter = 1667, accuracy (avg) = 0.845783 (all), 0.853638 (pos), 0.837938 (neg) | |
| data reader: epoch = 0, batch = 1668 / 4040 | |
| iter = 1668, cls_loss (cur) = 0.384943, cls_loss (avg) = 0.337653, lr = 0.010000 | |
| iter = 1668, accuracy (cur) = 0.760000 (all), 0.708333 (pos), 0.807692 (neg) | |
| iter = 1668, accuracy (avg) = 0.844925 (all), 0.852185 (pos), 0.837636 (neg) | |
| data reader: epoch = 0, batch = 1669 / 4040 | |
| iter = 1669, cls_loss (cur) = 0.447963, cls_loss (avg) = 0.338756, lr = 0.010000 | |
| iter = 1669, accuracy (cur) = 0.800000 (all), 0.944444 (pos), 0.718750 (neg) | |
| iter = 1669, accuracy (avg) = 0.844476 (all), 0.853108 (pos), 0.836447 (neg) | |
| data reader: epoch = 0, batch = 1670 / 4040 | |
| iter = 1670, cls_loss (cur) = 0.260164, cls_loss (avg) = 0.337970, lr = 0.010000 | |
| iter = 1670, accuracy (cur) = 0.920000 (all), 0.933333 (pos), 0.900000 (neg) | |
| iter = 1670, accuracy (avg) = 0.845231 (all), 0.853910 (pos), 0.837082 (neg) | |
| data reader: epoch = 0, batch = 1671 / 4040 | |
| iter = 1671, cls_loss (cur) = 0.412005, cls_loss (avg) = 0.338710, lr = 0.010000 | |
| iter = 1671, accuracy (cur) = 0.820000 (all), 0.851852 (pos), 0.782609 (neg) | |
| iter = 1671, accuracy (avg) = 0.844979 (all), 0.853890 (pos), 0.836538 (neg) | |
| data reader: epoch = 0, batch = 1672 / 4040 | |
| iter = 1672, cls_loss (cur) = 0.331874, cls_loss (avg) = 0.338642, lr = 0.010000 | |
| iter = 1672, accuracy (cur) = 0.880000 (all), 0.789474 (pos), 0.935484 (neg) | |
| iter = 1672, accuracy (avg) = 0.845329 (all), 0.853246 (pos), 0.837527 (neg) | |
| data reader: epoch = 0, batch = 1673 / 4040 | |
| iter = 1673, cls_loss (cur) = 0.464069, cls_loss (avg) = 0.339896, lr = 0.010000 | |
| iter = 1673, accuracy (cur) = 0.760000 (all), 0.818182 (pos), 0.714286 (neg) | |
| iter = 1673, accuracy (avg) = 0.844476 (all), 0.852895 (pos), 0.836295 (neg) | |
| data reader: epoch = 0, batch = 1674 / 4040 | |
| iter = 1674, cls_loss (cur) = 0.409676, cls_loss (avg) = 0.340594, lr = 0.010000 | |
| iter = 1674, accuracy (cur) = 0.780000 (all), 0.863636 (pos), 0.714286 (neg) | |
| iter = 1674, accuracy (avg) = 0.843831 (all), 0.853002 (pos), 0.835075 (neg) | |
| data reader: epoch = 0, batch = 1675 / 4040 | |
| iter = 1675, cls_loss (cur) = 0.294697, cls_loss (avg) = 0.340135, lr = 0.010000 | |
| iter = 1675, accuracy (cur) = 0.900000 (all), 1.000000 (pos), 0.814815 (neg) | |
| iter = 1675, accuracy (avg) = 0.844393 (all), 0.854472 (pos), 0.834872 (neg) | |
| data reader: epoch = 0, batch = 1676 / 4040 | |
| iter = 1676, cls_loss (cur) = 0.240380, cls_loss (avg) = 0.339138, lr = 0.010000 | |
| iter = 1676, accuracy (cur) = 0.920000 (all), 0.952381 (pos), 0.896552 (neg) | |
| iter = 1676, accuracy (avg) = 0.845149 (all), 0.855451 (pos), 0.835489 (neg) | |
| data reader: epoch = 0, batch = 1677 / 4040 | |
| iter = 1677, cls_loss (cur) = 0.377901, cls_loss (avg) = 0.339525, lr = 0.010000 | |
| iter = 1677, accuracy (cur) = 0.780000 (all), 0.705882 (pos), 0.937500 (neg) | |
| iter = 1677, accuracy (avg) = 0.844497 (all), 0.853956 (pos), 0.836509 (neg) | |
| data reader: epoch = 0, batch = 1678 / 4040 | |
| iter = 1678, cls_loss (cur) = 0.395869, cls_loss (avg) = 0.340089, lr = 0.010000 | |
| iter = 1678, accuracy (cur) = 0.820000 (all), 0.880000 (pos), 0.760000 (neg) | |
| iter = 1678, accuracy (avg) = 0.844253 (all), 0.854216 (pos), 0.835744 (neg) | |
| data reader: epoch = 0, batch = 1679 / 4040 | |
| iter = 1679, cls_loss (cur) = 0.330445, cls_loss (avg) = 0.339992, lr = 0.010000 | |
| iter = 1679, accuracy (cur) = 0.880000 (all), 0.827586 (pos), 0.952381 (neg) | |
| iter = 1679, accuracy (avg) = 0.844610 (all), 0.853950 (pos), 0.836910 (neg) | |
| data reader: epoch = 0, batch = 1680 / 4040 | |
| iter = 1680, cls_loss (cur) = 0.359837, cls_loss (avg) = 0.340191, lr = 0.010000 | |
| iter = 1680, accuracy (cur) = 0.880000 (all), 0.750000 (pos), 1.000000 (neg) | |
| iter = 1680, accuracy (avg) = 0.844964 (all), 0.852910 (pos), 0.838541 (neg) | |
| data reader: epoch = 0, batch = 1681 / 4040 | |
| iter = 1681, cls_loss (cur) = 0.366738, cls_loss (avg) = 0.340456, lr = 0.010000 | |
| iter = 1681, accuracy (cur) = 0.780000 (all), 0.782609 (pos), 0.777778 (neg) | |
| iter = 1681, accuracy (avg) = 0.844314 (all), 0.852207 (pos), 0.837934 (neg) | |
| data reader: epoch = 0, batch = 1682 / 4040 | |
| iter = 1682, cls_loss (cur) = 0.247819, cls_loss (avg) = 0.339530, lr = 0.010000 | |
| iter = 1682, accuracy (cur) = 0.880000 (all), 0.875000 (pos), 0.888889 (neg) | |
| iter = 1682, accuracy (avg) = 0.844671 (all), 0.852435 (pos), 0.838443 (neg) | |
| data reader: epoch = 0, batch = 1683 / 4040 | |
| iter = 1683, cls_loss (cur) = 0.285150, cls_loss (avg) = 0.338986, lr = 0.010000 | |
| iter = 1683, accuracy (cur) = 0.920000 (all), 0.909091 (pos), 0.928571 (neg) | |
| iter = 1683, accuracy (avg) = 0.845424 (all), 0.853002 (pos), 0.839344 (neg) | |
| data reader: epoch = 0, batch = 1684 / 4040 | |
| iter = 1684, cls_loss (cur) = 0.348041, cls_loss (avg) = 0.339077, lr = 0.010000 | |
| iter = 1684, accuracy (cur) = 0.860000 (all), 0.894737 (pos), 0.838710 (neg) | |
| iter = 1684, accuracy (avg) = 0.845570 (all), 0.853419 (pos), 0.839338 (neg) | |
| data reader: epoch = 0, batch = 1685 / 4040 | |
| iter = 1685, cls_loss (cur) = 0.285450, cls_loss (avg) = 0.338540, lr = 0.010000 | |
| iter = 1685, accuracy (cur) = 0.900000 (all), 0.962963 (pos), 0.826087 (neg) | |
| iter = 1685, accuracy (avg) = 0.846114 (all), 0.854515 (pos), 0.839206 (neg) | |
| data reader: epoch = 0, batch = 1686 / 4040 | |
| iter = 1686, cls_loss (cur) = 0.399743, cls_loss (avg) = 0.339152, lr = 0.010000 | |
| iter = 1686, accuracy (cur) = 0.800000 (all), 0.894737 (pos), 0.741935 (neg) | |
| iter = 1686, accuracy (avg) = 0.845653 (all), 0.854917 (pos), 0.838233 (neg) | |
| data reader: epoch = 0, batch = 1687 / 4040 | |
| iter = 1687, cls_loss (cur) = 0.259865, cls_loss (avg) = 0.338360, lr = 0.010000 | |
| iter = 1687, accuracy (cur) = 0.920000 (all), 0.923077 (pos), 0.916667 (neg) | |
| iter = 1687, accuracy (avg) = 0.846397 (all), 0.855598 (pos), 0.839017 (neg) | |
| data reader: epoch = 0, batch = 1688 / 4040 | |
| iter = 1688, cls_loss (cur) = 0.481935, cls_loss (avg) = 0.339795, lr = 0.010000 | |
| iter = 1688, accuracy (cur) = 0.800000 (all), 0.875000 (pos), 0.730769 (neg) | |
| iter = 1688, accuracy (avg) = 0.845933 (all), 0.855792 (pos), 0.837935 (neg) | |
| data reader: epoch = 0, batch = 1689 / 4040 | |
| iter = 1689, cls_loss (cur) = 0.407720, cls_loss (avg) = 0.340475, lr = 0.010000 | |
| iter = 1689, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 1689, accuracy (avg) = 0.845873 (all), 0.855753 (pos), 0.837816 (neg) | |
| data reader: epoch = 0, batch = 1690 / 4040 | |
| iter = 1690, cls_loss (cur) = 0.409979, cls_loss (avg) = 0.341170, lr = 0.010000 | |
| iter = 1690, accuracy (cur) = 0.800000 (all), 0.809524 (pos), 0.793103 (neg) | |
| iter = 1690, accuracy (avg) = 0.845415 (all), 0.855291 (pos), 0.837369 (neg) | |
| data reader: epoch = 0, batch = 1691 / 4040 | |
| iter = 1691, cls_loss (cur) = 0.317841, cls_loss (avg) = 0.340936, lr = 0.010000 | |
| iter = 1691, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 1691, accuracy (avg) = 0.845961 (all), 0.855969 (pos), 0.837745 (neg) | |
| data reader: epoch = 0, batch = 1692 / 4040 | |
| iter = 1692, cls_loss (cur) = 0.295235, cls_loss (avg) = 0.340479, lr = 0.010000 | |
| iter = 1692, accuracy (cur) = 0.860000 (all), 0.809524 (pos), 0.896552 (neg) | |
| iter = 1692, accuracy (avg) = 0.846101 (all), 0.855504 (pos), 0.838333 (neg) | |
| data reader: epoch = 0, batch = 1693 / 4040 | |
| iter = 1693, cls_loss (cur) = 0.319046, cls_loss (avg) = 0.340265, lr = 0.010000 | |
| iter = 1693, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.857143 (neg) | |
| iter = 1693, accuracy (avg) = 0.845640 (all), 0.854222 (pos), 0.838522 (neg) | |
| data reader: epoch = 0, batch = 1694 / 4040 | |
| iter = 1694, cls_loss (cur) = 0.292122, cls_loss (avg) = 0.339783, lr = 0.010000 | |
| iter = 1694, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1694, accuracy (avg) = 0.845984 (all), 0.854810 (pos), 0.838655 (neg) | |
| data reader: epoch = 0, batch = 1695 / 4040 | |
| iter = 1695, cls_loss (cur) = 0.333013, cls_loss (avg) = 0.339716, lr = 0.010000 | |
| iter = 1695, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.923077 (neg) | |
| iter = 1695, accuracy (avg) = 0.846324 (all), 0.854595 (pos), 0.839499 (neg) | |
| data reader: epoch = 0, batch = 1696 / 4040 | |
| iter = 1696, cls_loss (cur) = 0.315427, cls_loss (avg) = 0.339473, lr = 0.010000 | |
| iter = 1696, accuracy (cur) = 0.860000 (all), 0.866667 (pos), 0.850000 (neg) | |
| iter = 1696, accuracy (avg) = 0.846461 (all), 0.854716 (pos), 0.839604 (neg) | |
| data reader: epoch = 0, batch = 1697 / 4040 | |
| iter = 1697, cls_loss (cur) = 0.324948, cls_loss (avg) = 0.339328, lr = 0.010000 | |
| iter = 1697, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 1697, accuracy (avg) = 0.846196 (all), 0.853861 (pos), 0.839958 (neg) | |
| data reader: epoch = 0, batch = 1698 / 4040 | |
| iter = 1698, cls_loss (cur) = 0.326241, cls_loss (avg) = 0.339197, lr = 0.010000 | |
| iter = 1698, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 1698, accuracy (avg) = 0.846134 (all), 0.853784 (pos), 0.839892 (neg) | |
| data reader: epoch = 0, batch = 1699 / 4040 | |
| iter = 1699, cls_loss (cur) = 0.321842, cls_loss (avg) = 0.339023, lr = 0.010000 | |
| iter = 1699, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 1699, accuracy (avg) = 0.846073 (all), 0.853163 (pos), 0.840339 (neg) | |
| data reader: epoch = 0, batch = 1700 / 4040 | |
| iter = 1700, cls_loss (cur) = 0.350858, cls_loss (avg) = 0.339142, lr = 0.010000 | |
| iter = 1700, accuracy (cur) = 0.840000 (all), 0.720000 (pos), 0.960000 (neg) | |
| iter = 1700, accuracy (avg) = 0.846012 (all), 0.851831 (pos), 0.841536 (neg) | |
| data reader: epoch = 0, batch = 1701 / 4040 | |
| iter = 1701, cls_loss (cur) = 0.314736, cls_loss (avg) = 0.338898, lr = 0.010000 | |
| iter = 1701, accuracy (cur) = 0.880000 (all), 0.904762 (pos), 0.862069 (neg) | |
| iter = 1701, accuracy (avg) = 0.846352 (all), 0.852361 (pos), 0.841741 (neg) | |
| data reader: epoch = 0, batch = 1702 / 4040 | |
| iter = 1702, cls_loss (cur) = 0.376084, cls_loss (avg) = 0.339269, lr = 0.010000 | |
| iter = 1702, accuracy (cur) = 0.860000 (all), 0.923077 (pos), 0.791667 (neg) | |
| iter = 1702, accuracy (avg) = 0.846488 (all), 0.853068 (pos), 0.841240 (neg) | |
| data reader: epoch = 0, batch = 1703 / 4040 | |
| iter = 1703, cls_loss (cur) = 0.280098, cls_loss (avg) = 0.338678, lr = 0.010000 | |
| iter = 1703, accuracy (cur) = 0.900000 (all), 0.809524 (pos), 0.965517 (neg) | |
| iter = 1703, accuracy (avg) = 0.847023 (all), 0.852632 (pos), 0.842483 (neg) | |
| data reader: epoch = 0, batch = 1704 / 4040 | |
| iter = 1704, cls_loss (cur) = 0.270196, cls_loss (avg) = 0.337993, lr = 0.010000 | |
| iter = 1704, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 1704, accuracy (avg) = 0.847353 (all), 0.852567 (pos), 0.843225 (neg) | |
| data reader: epoch = 0, batch = 1705 / 4040 | |
| iter = 1705, cls_loss (cur) = 0.242350, cls_loss (avg) = 0.337036, lr = 0.010000 | |
| iter = 1705, accuracy (cur) = 0.920000 (all), 0.863636 (pos), 0.964286 (neg) | |
| iter = 1705, accuracy (avg) = 0.848080 (all), 0.852678 (pos), 0.844435 (neg) | |
| data reader: epoch = 0, batch = 1706 / 4040 | |
| iter = 1706, cls_loss (cur) = 0.280556, cls_loss (avg) = 0.336472, lr = 0.010000 | |
| iter = 1706, accuracy (cur) = 0.860000 (all), 0.842105 (pos), 0.870968 (neg) | |
| iter = 1706, accuracy (avg) = 0.848199 (all), 0.852572 (pos), 0.844701 (neg) | |
| data reader: epoch = 0, batch = 1707 / 4040 | |
| iter = 1707, cls_loss (cur) = 0.458679, cls_loss (avg) = 0.337694, lr = 0.010000 | |
| iter = 1707, accuracy (cur) = 0.740000 (all), 0.909091 (pos), 0.607143 (neg) | |
| iter = 1707, accuracy (avg) = 0.847117 (all), 0.853138 (pos), 0.842325 (neg) | |
| data reader: epoch = 0, batch = 1708 / 4040 | |
| iter = 1708, cls_loss (cur) = 0.193261, cls_loss (avg) = 0.336249, lr = 0.010000 | |
| iter = 1708, accuracy (cur) = 0.960000 (all), 0.933333 (pos), 1.000000 (neg) | |
| iter = 1708, accuracy (avg) = 0.848246 (all), 0.853940 (pos), 0.843902 (neg) | |
| data reader: epoch = 0, batch = 1709 / 4040 | |
| iter = 1709, cls_loss (cur) = 0.294523, cls_loss (avg) = 0.335832, lr = 0.010000 | |
| iter = 1709, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.923077 (neg) | |
| iter = 1709, accuracy (avg) = 0.848563 (all), 0.853734 (pos), 0.844694 (neg) | |
| data reader: epoch = 0, batch = 1710 / 4040 | |
| iter = 1710, cls_loss (cur) = 0.476478, cls_loss (avg) = 0.337239, lr = 0.010000 | |
| iter = 1710, accuracy (cur) = 0.760000 (all), 0.727273 (pos), 0.785714 (neg) | |
| iter = 1710, accuracy (avg) = 0.847678 (all), 0.852469 (pos), 0.844104 (neg) | |
| data reader: epoch = 0, batch = 1711 / 4040 | |
| iter = 1711, cls_loss (cur) = 0.260784, cls_loss (avg) = 0.336474, lr = 0.010000 | |
| iter = 1711, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 1711, accuracy (avg) = 0.848201 (all), 0.853175 (pos), 0.844413 (neg) | |
| data reader: epoch = 0, batch = 1712 / 4040 | |
| iter = 1712, cls_loss (cur) = 0.301856, cls_loss (avg) = 0.336128, lr = 0.010000 | |
| iter = 1712, accuracy (cur) = 0.860000 (all), 0.782609 (pos), 0.925926 (neg) | |
| iter = 1712, accuracy (avg) = 0.848319 (all), 0.852469 (pos), 0.845228 (neg) | |
| data reader: epoch = 0, batch = 1713 / 4040 | |
| iter = 1713, cls_loss (cur) = 0.327916, cls_loss (avg) = 0.336046, lr = 0.010000 | |
| iter = 1713, accuracy (cur) = 0.860000 (all), 0.777778 (pos), 0.956522 (neg) | |
| iter = 1713, accuracy (avg) = 0.848436 (all), 0.851722 (pos), 0.846341 (neg) | |
| data reader: epoch = 0, batch = 1714 / 4040 | |
| iter = 1714, cls_loss (cur) = 0.329211, cls_loss (avg) = 0.335977, lr = 0.010000 | |
| iter = 1714, accuracy (cur) = 0.880000 (all), 0.827586 (pos), 0.952381 (neg) | |
| iter = 1714, accuracy (avg) = 0.848751 (all), 0.851481 (pos), 0.847401 (neg) | |
| data reader: epoch = 0, batch = 1715 / 4040 | |
| iter = 1715, cls_loss (cur) = 0.233963, cls_loss (avg) = 0.334957, lr = 0.010000 | |
| iter = 1715, accuracy (cur) = 0.920000 (all), 0.880000 (pos), 0.960000 (neg) | |
| iter = 1715, accuracy (avg) = 0.849464 (all), 0.851766 (pos), 0.848527 (neg) | |
| data reader: epoch = 0, batch = 1716 / 4040 | |
| iter = 1716, cls_loss (cur) = 0.423648, cls_loss (avg) = 0.335844, lr = 0.010000 | |
| iter = 1716, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1716, accuracy (avg) = 0.849169 (all), 0.851582 (pos), 0.848119 (neg) | |
| data reader: epoch = 0, batch = 1717 / 4040 | |
| iter = 1717, cls_loss (cur) = 0.485001, cls_loss (avg) = 0.337336, lr = 0.010000 | |
| iter = 1717, accuracy (cur) = 0.820000 (all), 0.850000 (pos), 0.800000 (neg) | |
| iter = 1717, accuracy (avg) = 0.848877 (all), 0.851566 (pos), 0.847638 (neg) | |
| data reader: epoch = 0, batch = 1718 / 4040 | |
| iter = 1718, cls_loss (cur) = 0.284203, cls_loss (avg) = 0.336804, lr = 0.010000 | |
| iter = 1718, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 1718, accuracy (avg) = 0.849189 (all), 0.851512 (pos), 0.848328 (neg) | |
| data reader: epoch = 0, batch = 1719 / 4040 | |
| iter = 1719, cls_loss (cur) = 0.278800, cls_loss (avg) = 0.336224, lr = 0.010000 | |
| iter = 1719, accuracy (cur) = 0.880000 (all), 0.952381 (pos), 0.827586 (neg) | |
| iter = 1719, accuracy (avg) = 0.849497 (all), 0.852521 (pos), 0.848121 (neg) | |
| data reader: epoch = 0, batch = 1720 / 4040 | |
| iter = 1720, cls_loss (cur) = 0.331767, cls_loss (avg) = 0.336180, lr = 0.010000 | |
| iter = 1720, accuracy (cur) = 0.840000 (all), 0.880000 (pos), 0.800000 (neg) | |
| iter = 1720, accuracy (avg) = 0.849402 (all), 0.852795 (pos), 0.847639 (neg) | |
| data reader: epoch = 0, batch = 1721 / 4040 | |
| iter = 1721, cls_loss (cur) = 0.364103, cls_loss (avg) = 0.336459, lr = 0.010000 | |
| iter = 1721, accuracy (cur) = 0.820000 (all), 0.761905 (pos), 0.862069 (neg) | |
| iter = 1721, accuracy (avg) = 0.849108 (all), 0.851887 (pos), 0.847784 (neg) | |
| data reader: epoch = 0, batch = 1722 / 4040 | |
| iter = 1722, cls_loss (cur) = 0.405150, cls_loss (avg) = 0.337146, lr = 0.010000 | |
| iter = 1722, accuracy (cur) = 0.820000 (all), 0.827586 (pos), 0.809524 (neg) | |
| iter = 1722, accuracy (avg) = 0.848817 (all), 0.851644 (pos), 0.847401 (neg) | |
| data reader: epoch = 0, batch = 1723 / 4040 | |
| iter = 1723, cls_loss (cur) = 0.310749, cls_loss (avg) = 0.336882, lr = 0.010000 | |
| iter = 1723, accuracy (cur) = 0.860000 (all), 0.761905 (pos), 0.931034 (neg) | |
| iter = 1723, accuracy (avg) = 0.848929 (all), 0.850746 (pos), 0.848237 (neg) | |
| data reader: epoch = 0, batch = 1724 / 4040 | |
| iter = 1724, cls_loss (cur) = 0.405444, cls_loss (avg) = 0.337568, lr = 0.010000 | |
| iter = 1724, accuracy (cur) = 0.820000 (all), 0.892857 (pos), 0.727273 (neg) | |
| iter = 1724, accuracy (avg) = 0.848639 (all), 0.851167 (pos), 0.847028 (neg) | |
| data reader: epoch = 0, batch = 1725 / 4040 | |
| iter = 1725, cls_loss (cur) = 0.278671, cls_loss (avg) = 0.336979, lr = 0.010000 | |
| iter = 1725, accuracy (cur) = 0.880000 (all), 0.884615 (pos), 0.875000 (neg) | |
| iter = 1725, accuracy (avg) = 0.848953 (all), 0.851502 (pos), 0.847308 (neg) | |
| data reader: epoch = 0, batch = 1726 / 4040 | |
| iter = 1726, cls_loss (cur) = 0.395041, cls_loss (avg) = 0.337559, lr = 0.010000 | |
| iter = 1726, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 1726, accuracy (avg) = 0.848663 (all), 0.850679 (pos), 0.847584 (neg) | |
| data reader: epoch = 0, batch = 1727 / 4040 | |
| iter = 1727, cls_loss (cur) = 0.399165, cls_loss (avg) = 0.338175, lr = 0.010000 | |
| iter = 1727, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 1727, accuracy (avg) = 0.848377 (all), 0.849772 (pos), 0.847909 (neg) | |
| data reader: epoch = 0, batch = 1728 / 4040 | |
| iter = 1728, cls_loss (cur) = 0.339434, cls_loss (avg) = 0.338188, lr = 0.010000 | |
| iter = 1728, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 1728, accuracy (avg) = 0.848693 (all), 0.850505 (pos), 0.847763 (neg) | |
| data reader: epoch = 0, batch = 1729 / 4040 | |
| iter = 1729, cls_loss (cur) = 0.268548, cls_loss (avg) = 0.337491, lr = 0.010000 | |
| iter = 1729, accuracy (cur) = 0.880000 (all), 0.961538 (pos), 0.791667 (neg) | |
| iter = 1729, accuracy (avg) = 0.849006 (all), 0.851616 (pos), 0.847202 (neg) | |
| data reader: epoch = 0, batch = 1730 / 4040 | |
| iter = 1730, cls_loss (cur) = 0.352997, cls_loss (avg) = 0.337647, lr = 0.010000 | |
| iter = 1730, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1730, accuracy (avg) = 0.848916 (all), 0.851176 (pos), 0.847480 (neg) | |
| data reader: epoch = 0, batch = 1731 / 4040 | |
| iter = 1731, cls_loss (cur) = 0.327155, cls_loss (avg) = 0.337542, lr = 0.010000 | |
| iter = 1731, accuracy (cur) = 0.880000 (all), 0.952381 (pos), 0.827586 (neg) | |
| iter = 1731, accuracy (avg) = 0.849227 (all), 0.852188 (pos), 0.847281 (neg) | |
| data reader: epoch = 0, batch = 1732 / 4040 | |
| iter = 1732, cls_loss (cur) = 0.379256, cls_loss (avg) = 0.337959, lr = 0.010000 | |
| iter = 1732, accuracy (cur) = 0.820000 (all), 0.840000 (pos), 0.800000 (neg) | |
| iter = 1732, accuracy (avg) = 0.848934 (all), 0.852067 (pos), 0.846808 (neg) | |
| data reader: epoch = 0, batch = 1733 / 4040 | |
| iter = 1733, cls_loss (cur) = 0.205065, cls_loss (avg) = 0.336630, lr = 0.010000 | |
| iter = 1733, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.909091 (neg) | |
| iter = 1733, accuracy (avg) = 0.850045 (all), 0.853546 (pos), 0.847431 (neg) | |
| data reader: epoch = 0, batch = 1734 / 4040 | |
| iter = 1734, cls_loss (cur) = 0.434932, cls_loss (avg) = 0.337613, lr = 0.010000 | |
| iter = 1734, accuracy (cur) = 0.760000 (all), 0.766667 (pos), 0.750000 (neg) | |
| iter = 1734, accuracy (avg) = 0.849145 (all), 0.852677 (pos), 0.846457 (neg) | |
| data reader: epoch = 0, batch = 1735 / 4040 | |
| iter = 1735, cls_loss (cur) = 0.332731, cls_loss (avg) = 0.337564, lr = 0.010000 | |
| iter = 1735, accuracy (cur) = 0.860000 (all), 0.850000 (pos), 0.866667 (neg) | |
| iter = 1735, accuracy (avg) = 0.849253 (all), 0.852650 (pos), 0.846659 (neg) | |
| data reader: epoch = 0, batch = 1736 / 4040 | |
| iter = 1736, cls_loss (cur) = 0.276441, cls_loss (avg) = 0.336953, lr = 0.010000 | |
| iter = 1736, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.931034 (neg) | |
| iter = 1736, accuracy (avg) = 0.849761 (all), 0.852695 (pos), 0.847503 (neg) | |
| data reader: epoch = 0, batch = 1737 / 4040 | |
| iter = 1737, cls_loss (cur) = 0.382931, cls_loss (avg) = 0.337413, lr = 0.010000 | |
| iter = 1737, accuracy (cur) = 0.840000 (all), 1.000000 (pos), 0.703704 (neg) | |
| iter = 1737, accuracy (avg) = 0.849663 (all), 0.854168 (pos), 0.846065 (neg) | |
| data reader: epoch = 0, batch = 1738 / 4040 | |
| iter = 1738, cls_loss (cur) = 0.278657, cls_loss (avg) = 0.336825, lr = 0.010000 | |
| iter = 1738, accuracy (cur) = 0.920000 (all), 0.884615 (pos), 0.958333 (neg) | |
| iter = 1738, accuracy (avg) = 0.850366 (all), 0.854473 (pos), 0.847187 (neg) | |
| data reader: epoch = 0, batch = 1739 / 4040 | |
| iter = 1739, cls_loss (cur) = 0.443247, cls_loss (avg) = 0.337889, lr = 0.010000 | |
| iter = 1739, accuracy (cur) = 0.860000 (all), 0.800000 (pos), 0.920000 (neg) | |
| iter = 1739, accuracy (avg) = 0.850463 (all), 0.853928 (pos), 0.847915 (neg) | |
| data reader: epoch = 0, batch = 1740 / 4040 | |
| iter = 1740, cls_loss (cur) = 0.243669, cls_loss (avg) = 0.336947, lr = 0.010000 | |
| iter = 1740, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 1740, accuracy (avg) = 0.850758 (all), 0.853789 (pos), 0.848636 (neg) | |
| data reader: epoch = 0, batch = 1741 / 4040 | |
| iter = 1741, cls_loss (cur) = 0.242243, cls_loss (avg) = 0.336000, lr = 0.010000 | |
| iter = 1741, accuracy (cur) = 0.940000 (all), 0.896552 (pos), 1.000000 (neg) | |
| iter = 1741, accuracy (avg) = 0.851651 (all), 0.854216 (pos), 0.850150 (neg) | |
| data reader: epoch = 0, batch = 1742 / 4040 | |
| iter = 1742, cls_loss (cur) = 0.265681, cls_loss (avg) = 0.335297, lr = 0.010000 | |
| iter = 1742, accuracy (cur) = 0.920000 (all), 0.916667 (pos), 0.923077 (neg) | |
| iter = 1742, accuracy (avg) = 0.852334 (all), 0.854841 (pos), 0.850879 (neg) | |
| data reader: epoch = 0, batch = 1743 / 4040 | |
| iter = 1743, cls_loss (cur) = 0.366945, cls_loss (avg) = 0.335613, lr = 0.010000 | |
| iter = 1743, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 1743, accuracy (avg) = 0.851811 (all), 0.854292 (pos), 0.850370 (neg) | |
| data reader: epoch = 0, batch = 1744 / 4040 | |
| iter = 1744, cls_loss (cur) = 0.331143, cls_loss (avg) = 0.335569, lr = 0.010000 | |
| iter = 1744, accuracy (cur) = 0.820000 (all), 0.928571 (pos), 0.681818 (neg) | |
| iter = 1744, accuracy (avg) = 0.851493 (all), 0.855035 (pos), 0.848685 (neg) | |
| data reader: epoch = 0, batch = 1745 / 4040 | |
| iter = 1745, cls_loss (cur) = 0.306015, cls_loss (avg) = 0.335273, lr = 0.010000 | |
| iter = 1745, accuracy (cur) = 0.880000 (all), 0.875000 (pos), 0.884615 (neg) | |
| iter = 1745, accuracy (avg) = 0.851778 (all), 0.855235 (pos), 0.849044 (neg) | |
| data reader: epoch = 0, batch = 1746 / 4040 | |
| iter = 1746, cls_loss (cur) = 0.302301, cls_loss (avg) = 0.334943, lr = 0.010000 | |
| iter = 1746, accuracy (cur) = 0.880000 (all), 0.894737 (pos), 0.870968 (neg) | |
| iter = 1746, accuracy (avg) = 0.852060 (all), 0.855630 (pos), 0.849263 (neg) | |
| data reader: epoch = 0, batch = 1747 / 4040 | |
| iter = 1747, cls_loss (cur) = 0.395803, cls_loss (avg) = 0.335552, lr = 0.010000 | |
| iter = 1747, accuracy (cur) = 0.820000 (all), 0.857143 (pos), 0.772727 (neg) | |
| iter = 1747, accuracy (avg) = 0.851739 (all), 0.855645 (pos), 0.848498 (neg) | |
| data reader: epoch = 0, batch = 1748 / 4040 | |
| iter = 1748, cls_loss (cur) = 0.286137, cls_loss (avg) = 0.335058, lr = 0.010000 | |
| iter = 1748, accuracy (cur) = 0.960000 (all), 0.954545 (pos), 0.964286 (neg) | |
| iter = 1748, accuracy (avg) = 0.852822 (all), 0.856634 (pos), 0.849656 (neg) | |
| data reader: epoch = 0, batch = 1749 / 4040 | |
| iter = 1749, cls_loss (cur) = 0.356660, cls_loss (avg) = 0.335274, lr = 0.010000 | |
| iter = 1749, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 1749, accuracy (avg) = 0.853094 (all), 0.856996 (pos), 0.849796 (neg) | |
| data reader: epoch = 0, batch = 1750 / 4040 | |
| iter = 1750, cls_loss (cur) = 0.269186, cls_loss (avg) = 0.334613, lr = 0.010000 | |
| iter = 1750, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.875000 (neg) | |
| iter = 1750, accuracy (avg) = 0.853363 (all), 0.857315 (pos), 0.850048 (neg) | |
| data reader: epoch = 0, batch = 1751 / 4040 | |
| iter = 1751, cls_loss (cur) = 0.452477, cls_loss (avg) = 0.335792, lr = 0.010000 | |
| iter = 1751, accuracy (cur) = 0.840000 (all), 0.909091 (pos), 0.785714 (neg) | |
| iter = 1751, accuracy (avg) = 0.853229 (all), 0.857833 (pos), 0.849404 (neg) | |
| data reader: epoch = 0, batch = 1752 / 4040 | |
| iter = 1752, cls_loss (cur) = 0.264697, cls_loss (avg) = 0.335081, lr = 0.010000 | |
| iter = 1752, accuracy (cur) = 0.900000 (all), 0.913043 (pos), 0.888889 (neg) | |
| iter = 1752, accuracy (avg) = 0.853697 (all), 0.858385 (pos), 0.849799 (neg) | |
| data reader: epoch = 0, batch = 1753 / 4040 | |
| iter = 1753, cls_loss (cur) = 0.334157, cls_loss (avg) = 0.335071, lr = 0.010000 | |
| iter = 1753, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.800000 (neg) | |
| iter = 1753, accuracy (avg) = 0.853360 (all), 0.858135 (pos), 0.849301 (neg) | |
| data reader: epoch = 0, batch = 1754 / 4040 | |
| iter = 1754, cls_loss (cur) = 0.242298, cls_loss (avg) = 0.334144, lr = 0.010000 | |
| iter = 1754, accuracy (cur) = 0.940000 (all), 0.962963 (pos), 0.913043 (neg) | |
| iter = 1754, accuracy (avg) = 0.854226 (all), 0.859183 (pos), 0.849939 (neg) | |
| data reader: epoch = 0, batch = 1755 / 4040 | |
| iter = 1755, cls_loss (cur) = 0.303148, cls_loss (avg) = 0.333834, lr = 0.010000 | |
| iter = 1755, accuracy (cur) = 0.920000 (all), 0.888889 (pos), 0.956522 (neg) | |
| iter = 1755, accuracy (avg) = 0.854884 (all), 0.859480 (pos), 0.851004 (neg) | |
| data reader: epoch = 0, batch = 1756 / 4040 | |
| iter = 1756, cls_loss (cur) = 0.363992, cls_loss (avg) = 0.334135, lr = 0.010000 | |
| iter = 1756, accuracy (cur) = 0.840000 (all), 0.900000 (pos), 0.800000 (neg) | |
| iter = 1756, accuracy (avg) = 0.854735 (all), 0.859885 (pos), 0.850494 (neg) | |
| data reader: epoch = 0, batch = 1757 / 4040 | |
| iter = 1757, cls_loss (cur) = 0.331102, cls_loss (avg) = 0.334105, lr = 0.010000 | |
| iter = 1757, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 1757, accuracy (avg) = 0.854988 (all), 0.859468 (pos), 0.851275 (neg) | |
| data reader: epoch = 0, batch = 1758 / 4040 | |
| iter = 1758, cls_loss (cur) = 0.299125, cls_loss (avg) = 0.333755, lr = 0.010000 | |
| iter = 1758, accuracy (cur) = 0.860000 (all), 0.791667 (pos), 0.923077 (neg) | |
| iter = 1758, accuracy (avg) = 0.855038 (all), 0.858790 (pos), 0.851993 (neg) | |
| data reader: epoch = 0, batch = 1759 / 4040 | |
| iter = 1759, cls_loss (cur) = 0.309167, cls_loss (avg) = 0.333509, lr = 0.010000 | |
| iter = 1759, accuracy (cur) = 0.840000 (all), 0.823529 (pos), 0.875000 (neg) | |
| iter = 1759, accuracy (avg) = 0.854888 (all), 0.858437 (pos), 0.852223 (neg) | |
| data reader: epoch = 0, batch = 1760 / 4040 | |
| iter = 1760, cls_loss (cur) = 0.419017, cls_loss (avg) = 0.334364, lr = 0.010000 | |
| iter = 1760, accuracy (cur) = 0.780000 (all), 0.774194 (pos), 0.789474 (neg) | |
| iter = 1760, accuracy (avg) = 0.854139 (all), 0.857595 (pos), 0.851596 (neg) | |
| data reader: epoch = 0, batch = 1761 / 4040 | |
| iter = 1761, cls_loss (cur) = 0.434658, cls_loss (avg) = 0.335367, lr = 0.010000 | |
| iter = 1761, accuracy (cur) = 0.760000 (all), 0.760000 (pos), 0.760000 (neg) | |
| iter = 1761, accuracy (avg) = 0.853197 (all), 0.856619 (pos), 0.850680 (neg) | |
| data reader: epoch = 0, batch = 1762 / 4040 | |
| iter = 1762, cls_loss (cur) = 0.359940, cls_loss (avg) = 0.335613, lr = 0.010000 | |
| iter = 1762, accuracy (cur) = 0.780000 (all), 0.840000 (pos), 0.720000 (neg) | |
| iter = 1762, accuracy (avg) = 0.852465 (all), 0.856453 (pos), 0.849373 (neg) | |
| data reader: epoch = 0, batch = 1763 / 4040 | |
| iter = 1763, cls_loss (cur) = 0.328492, cls_loss (avg) = 0.335542, lr = 0.010000 | |
| iter = 1763, accuracy (cur) = 0.840000 (all), 0.894737 (pos), 0.806452 (neg) | |
| iter = 1763, accuracy (avg) = 0.852341 (all), 0.856836 (pos), 0.848944 (neg) | |
| data reader: epoch = 0, batch = 1764 / 4040 | |
| iter = 1764, cls_loss (cur) = 0.427485, cls_loss (avg) = 0.336461, lr = 0.010000 | |
| iter = 1764, accuracy (cur) = 0.800000 (all), 0.826087 (pos), 0.777778 (neg) | |
| iter = 1764, accuracy (avg) = 0.851817 (all), 0.856528 (pos), 0.848232 (neg) | |
| data reader: epoch = 0, batch = 1765 / 4040 | |
| iter = 1765, cls_loss (cur) = 0.377818, cls_loss (avg) = 0.336875, lr = 0.010000 | |
| iter = 1765, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.884615 (neg) | |
| iter = 1765, accuracy (avg) = 0.851499 (all), 0.855463 (pos), 0.848596 (neg) | |
| data reader: epoch = 0, batch = 1766 / 4040 | |
| iter = 1766, cls_loss (cur) = 0.288836, cls_loss (avg) = 0.336394, lr = 0.010000 | |
| iter = 1766, accuracy (cur) = 0.880000 (all), 0.807692 (pos), 0.958333 (neg) | |
| iter = 1766, accuracy (avg) = 0.851784 (all), 0.854985 (pos), 0.849693 (neg) | |
| data reader: epoch = 0, batch = 1767 / 4040 | |
| iter = 1767, cls_loss (cur) = 0.443310, cls_loss (avg) = 0.337464, lr = 0.010000 | |
| iter = 1767, accuracy (cur) = 0.760000 (all), 0.714286 (pos), 0.818182 (neg) | |
| iter = 1767, accuracy (avg) = 0.850866 (all), 0.853578 (pos), 0.849378 (neg) | |
| data reader: epoch = 0, batch = 1768 / 4040 | |
| iter = 1768, cls_loss (cur) = 0.246548, cls_loss (avg) = 0.336554, lr = 0.010000 | |
| iter = 1768, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.823529 (neg) | |
| iter = 1768, accuracy (avg) = 0.851158 (all), 0.854133 (pos), 0.849120 (neg) | |
| data reader: epoch = 0, batch = 1769 / 4040 | |
| iter = 1769, cls_loss (cur) = 0.262916, cls_loss (avg) = 0.335818, lr = 0.010000 | |
| iter = 1769, accuracy (cur) = 0.900000 (all), 0.964286 (pos), 0.818182 (neg) | |
| iter = 1769, accuracy (avg) = 0.851646 (all), 0.855235 (pos), 0.848810 (neg) | |
| data reader: epoch = 0, batch = 1770 / 4040 | |
| iter = 1770, cls_loss (cur) = 0.338646, cls_loss (avg) = 0.335846, lr = 0.010000 | |
| iter = 1770, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 1770, accuracy (avg) = 0.851530 (all), 0.855083 (pos), 0.848722 (neg) | |
| data reader: epoch = 0, batch = 1771 / 4040 | |
| iter = 1771, cls_loss (cur) = 0.382121, cls_loss (avg) = 0.336309, lr = 0.010000 | |
| iter = 1771, accuracy (cur) = 0.820000 (all), 0.866667 (pos), 0.750000 (neg) | |
| iter = 1771, accuracy (avg) = 0.851214 (all), 0.855198 (pos), 0.847735 (neg) | |
| data reader: epoch = 0, batch = 1772 / 4040 | |
| iter = 1772, cls_loss (cur) = 0.247915, cls_loss (avg) = 0.335425, lr = 0.010000 | |
| iter = 1772, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.875000 (neg) | |
| iter = 1772, accuracy (avg) = 0.852102 (all), 0.856646 (pos), 0.848008 (neg) | |
| data reader: epoch = 0, batch = 1773 / 4040 | |
| iter = 1773, cls_loss (cur) = 0.269975, cls_loss (avg) = 0.334771, lr = 0.010000 | |
| iter = 1773, accuracy (cur) = 0.900000 (all), 0.941176 (pos), 0.812500 (neg) | |
| iter = 1773, accuracy (avg) = 0.852581 (all), 0.857492 (pos), 0.847653 (neg) | |
| data reader: epoch = 0, batch = 1774 / 4040 | |
| iter = 1774, cls_loss (cur) = 0.354179, cls_loss (avg) = 0.334965, lr = 0.010000 | |
| iter = 1774, accuracy (cur) = 0.820000 (all), 0.944444 (pos), 0.750000 (neg) | |
| iter = 1774, accuracy (avg) = 0.852255 (all), 0.858361 (pos), 0.846676 (neg) | |
| data reader: epoch = 0, batch = 1775 / 4040 | |
| iter = 1775, cls_loss (cur) = 0.148852, cls_loss (avg) = 0.333104, lr = 0.010000 | |
| iter = 1775, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.923077 (neg) | |
| iter = 1775, accuracy (avg) = 0.853333 (all), 0.859778 (pos), 0.847440 (neg) | |
| data reader: epoch = 0, batch = 1776 / 4040 | |
| iter = 1776, cls_loss (cur) = 0.195413, cls_loss (avg) = 0.331727, lr = 0.010000 | |
| iter = 1776, accuracy (cur) = 0.960000 (all), 0.969697 (pos), 0.941176 (neg) | |
| iter = 1776, accuracy (avg) = 0.854399 (all), 0.860877 (pos), 0.848377 (neg) | |
| data reader: epoch = 0, batch = 1777 / 4040 | |
| iter = 1777, cls_loss (cur) = 0.386076, cls_loss (avg) = 0.332270, lr = 0.010000 | |
| iter = 1777, accuracy (cur) = 0.840000 (all), 0.928571 (pos), 0.727273 (neg) | |
| iter = 1777, accuracy (avg) = 0.854255 (all), 0.861554 (pos), 0.847166 (neg) | |
| data reader: epoch = 0, batch = 1778 / 4040 | |
| iter = 1778, cls_loss (cur) = 0.298073, cls_loss (avg) = 0.331928, lr = 0.010000 | |
| iter = 1778, accuracy (cur) = 0.840000 (all), 0.916667 (pos), 0.769231 (neg) | |
| iter = 1778, accuracy (avg) = 0.854113 (all), 0.862105 (pos), 0.846387 (neg) | |
| data reader: epoch = 0, batch = 1779 / 4040 | |
| iter = 1779, cls_loss (cur) = 0.384687, cls_loss (avg) = 0.332456, lr = 0.010000 | |
| iter = 1779, accuracy (cur) = 0.800000 (all), 0.931034 (pos), 0.619048 (neg) | |
| iter = 1779, accuracy (avg) = 0.853572 (all), 0.862794 (pos), 0.844114 (neg) | |
| data reader: epoch = 0, batch = 1780 / 4040 | |
| iter = 1780, cls_loss (cur) = 0.384340, cls_loss (avg) = 0.332975, lr = 0.010000 | |
| iter = 1780, accuracy (cur) = 0.840000 (all), 0.814815 (pos), 0.869565 (neg) | |
| iter = 1780, accuracy (avg) = 0.853436 (all), 0.862314 (pos), 0.844368 (neg) | |
| data reader: epoch = 0, batch = 1781 / 4040 | |
| iter = 1781, cls_loss (cur) = 0.322574, cls_loss (avg) = 0.332871, lr = 0.010000 | |
| iter = 1781, accuracy (cur) = 0.800000 (all), 0.833333 (pos), 0.781250 (neg) | |
| iter = 1781, accuracy (avg) = 0.852902 (all), 0.862025 (pos), 0.843737 (neg) | |
| data reader: epoch = 0, batch = 1782 / 4040 | |
| iter = 1782, cls_loss (cur) = 0.302739, cls_loss (avg) = 0.332569, lr = 0.010000 | |
| iter = 1782, accuracy (cur) = 0.880000 (all), 0.928571 (pos), 0.818182 (neg) | |
| iter = 1782, accuracy (avg) = 0.853173 (all), 0.862690 (pos), 0.843481 (neg) | |
| data reader: epoch = 0, batch = 1783 / 4040 | |
| iter = 1783, cls_loss (cur) = 0.309943, cls_loss (avg) = 0.332343, lr = 0.010000 | |
| iter = 1783, accuracy (cur) = 0.840000 (all), 0.740741 (pos), 0.956522 (neg) | |
| iter = 1783, accuracy (avg) = 0.853041 (all), 0.861471 (pos), 0.844612 (neg) | |
| data reader: epoch = 0, batch = 1784 / 4040 | |
| iter = 1784, cls_loss (cur) = 0.366455, cls_loss (avg) = 0.332684, lr = 0.010000 | |
| iter = 1784, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 1784, accuracy (avg) = 0.853111 (all), 0.861374 (pos), 0.844861 (neg) | |
| data reader: epoch = 0, batch = 1785 / 4040 | |
| iter = 1785, cls_loss (cur) = 0.288401, cls_loss (avg) = 0.332241, lr = 0.010000 | |
| iter = 1785, accuracy (cur) = 0.840000 (all), 0.826087 (pos), 0.851852 (neg) | |
| iter = 1785, accuracy (avg) = 0.852979 (all), 0.861022 (pos), 0.844931 (neg) | |
| data reader: epoch = 0, batch = 1786 / 4040 | |
| iter = 1786, cls_loss (cur) = 0.313000, cls_loss (avg) = 0.332049, lr = 0.010000 | |
| iter = 1786, accuracy (cur) = 0.840000 (all), 0.821429 (pos), 0.863636 (neg) | |
| iter = 1786, accuracy (avg) = 0.852850 (all), 0.860626 (pos), 0.845118 (neg) | |
| data reader: epoch = 0, batch = 1787 / 4040 | |
| iter = 1787, cls_loss (cur) = 0.261794, cls_loss (avg) = 0.331346, lr = 0.010000 | |
| iter = 1787, accuracy (cur) = 0.880000 (all), 0.851852 (pos), 0.913043 (neg) | |
| iter = 1787, accuracy (avg) = 0.853121 (all), 0.860538 (pos), 0.845798 (neg) | |
| data reader: epoch = 0, batch = 1788 / 4040 | |
| iter = 1788, cls_loss (cur) = 0.228350, cls_loss (avg) = 0.330316, lr = 0.010000 | |
| iter = 1788, accuracy (cur) = 0.920000 (all), 0.909091 (pos), 0.928571 (neg) | |
| iter = 1788, accuracy (avg) = 0.853790 (all), 0.861023 (pos), 0.846625 (neg) | |
| data reader: epoch = 0, batch = 1789 / 4040 | |
| iter = 1789, cls_loss (cur) = 0.299450, cls_loss (avg) = 0.330008, lr = 0.010000 | |
| iter = 1789, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1789, accuracy (avg) = 0.853852 (all), 0.861163 (pos), 0.846621 (neg) | |
| data reader: epoch = 0, batch = 1790 / 4040 | |
| iter = 1790, cls_loss (cur) = 0.351805, cls_loss (avg) = 0.330226, lr = 0.010000 | |
| iter = 1790, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1790, accuracy (avg) = 0.853713 (all), 0.861302 (pos), 0.846231 (neg) | |
| data reader: epoch = 0, batch = 1791 / 4040 | |
| iter = 1791, cls_loss (cur) = 0.351664, cls_loss (avg) = 0.330440, lr = 0.010000 | |
| iter = 1791, accuracy (cur) = 0.860000 (all), 0.833333 (pos), 0.884615 (neg) | |
| iter = 1791, accuracy (avg) = 0.853776 (all), 0.861022 (pos), 0.846615 (neg) | |
| data reader: epoch = 0, batch = 1792 / 4040 | |
| iter = 1792, cls_loss (cur) = 0.299150, cls_loss (avg) = 0.330127, lr = 0.010000 | |
| iter = 1792, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 1792, accuracy (avg) = 0.854239 (all), 0.861578 (pos), 0.846995 (neg) | |
| data reader: epoch = 0, batch = 1793 / 4040 | |
| iter = 1793, cls_loss (cur) = 0.301920, cls_loss (avg) = 0.329845, lr = 0.010000 | |
| iter = 1793, accuracy (cur) = 0.860000 (all), 0.928571 (pos), 0.772727 (neg) | |
| iter = 1793, accuracy (avg) = 0.854296 (all), 0.862248 (pos), 0.846252 (neg) | |
| data reader: epoch = 0, batch = 1794 / 4040 | |
| iter = 1794, cls_loss (cur) = 0.323636, cls_loss (avg) = 0.329783, lr = 0.010000 | |
| iter = 1794, accuracy (cur) = 0.820000 (all), 0.727273 (pos), 0.892857 (neg) | |
| iter = 1794, accuracy (avg) = 0.853953 (all), 0.860898 (pos), 0.846719 (neg) | |
| data reader: epoch = 0, batch = 1795 / 4040 | |
| iter = 1795, cls_loss (cur) = 0.296338, cls_loss (avg) = 0.329449, lr = 0.010000 | |
| iter = 1795, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 1795, accuracy (avg) = 0.854214 (all), 0.861178 (pos), 0.846947 (neg) | |
| data reader: epoch = 0, batch = 1796 / 4040 | |
| iter = 1796, cls_loss (cur) = 0.218554, cls_loss (avg) = 0.328340, lr = 0.010000 | |
| iter = 1796, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.928571 (neg) | |
| iter = 1796, accuracy (avg) = 0.855272 (all), 0.862567 (pos), 0.847763 (neg) | |
| data reader: epoch = 0, batch = 1797 / 4040 | |
| iter = 1797, cls_loss (cur) = 0.165721, cls_loss (avg) = 0.326713, lr = 0.010000 | |
| iter = 1797, accuracy (cur) = 1.000000 (all), 1.000000 (pos), 1.000000 (neg) | |
| iter = 1797, accuracy (avg) = 0.856719 (all), 0.863941 (pos), 0.849286 (neg) | |
| data reader: epoch = 0, batch = 1798 / 4040 | |
| iter = 1798, cls_loss (cur) = 0.329749, cls_loss (avg) = 0.326744, lr = 0.010000 | |
| iter = 1798, accuracy (cur) = 0.860000 (all), 0.923077 (pos), 0.791667 (neg) | |
| iter = 1798, accuracy (avg) = 0.856752 (all), 0.864532 (pos), 0.848709 (neg) | |
| data reader: epoch = 0, batch = 1799 / 4040 | |
| iter = 1799, cls_loss (cur) = 0.353326, cls_loss (avg) = 0.327010, lr = 0.010000 | |
| iter = 1799, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.818182 (neg) | |
| iter = 1799, accuracy (avg) = 0.856584 (all), 0.864458 (pos), 0.848404 (neg) | |
| data reader: epoch = 0, batch = 1800 / 4040 | |
| iter = 1800, cls_loss (cur) = 0.401935, cls_loss (avg) = 0.327759, lr = 0.010000 | |
| iter = 1800, accuracy (cur) = 0.780000 (all), 0.730769 (pos), 0.833333 (neg) | |
| iter = 1800, accuracy (avg) = 0.855818 (all), 0.863121 (pos), 0.848253 (neg) | |
| data reader: epoch = 0, batch = 1801 / 4040 | |
| iter = 1801, cls_loss (cur) = 0.341473, cls_loss (avg) = 0.327896, lr = 0.010000 | |
| iter = 1801, accuracy (cur) = 0.880000 (all), 0.823529 (pos), 0.909091 (neg) | |
| iter = 1801, accuracy (avg) = 0.856060 (all), 0.862726 (pos), 0.848862 (neg) | |
| data reader: epoch = 0, batch = 1802 / 4040 | |
| iter = 1802, cls_loss (cur) = 0.320620, cls_loss (avg) = 0.327823, lr = 0.010000 | |
| iter = 1802, accuracy (cur) = 0.840000 (all), 0.894737 (pos), 0.806452 (neg) | |
| iter = 1802, accuracy (avg) = 0.855900 (all), 0.863046 (pos), 0.848438 (neg) | |
| data reader: epoch = 0, batch = 1803 / 4040 | |
| iter = 1803, cls_loss (cur) = 0.475530, cls_loss (avg) = 0.329300, lr = 0.010000 | |
| iter = 1803, accuracy (cur) = 0.820000 (all), 0.733333 (pos), 0.857143 (neg) | |
| iter = 1803, accuracy (avg) = 0.855541 (all), 0.861749 (pos), 0.848525 (neg) | |
| data reader: epoch = 0, batch = 1804 / 4040 | |
| iter = 1804, cls_loss (cur) = 0.310363, cls_loss (avg) = 0.329111, lr = 0.010000 | |
| iter = 1804, accuracy (cur) = 0.880000 (all), 0.875000 (pos), 0.884615 (neg) | |
| iter = 1804, accuracy (avg) = 0.855785 (all), 0.861881 (pos), 0.848886 (neg) | |
| data reader: epoch = 0, batch = 1805 / 4040 | |
| iter = 1805, cls_loss (cur) = 0.458243, cls_loss (avg) = 0.330402, lr = 0.010000 | |
| iter = 1805, accuracy (cur) = 0.760000 (all), 0.714286 (pos), 0.818182 (neg) | |
| iter = 1805, accuracy (avg) = 0.854827 (all), 0.860405 (pos), 0.848579 (neg) | |
| data reader: epoch = 0, batch = 1806 / 4040 | |
| iter = 1806, cls_loss (cur) = 0.416666, cls_loss (avg) = 0.331265, lr = 0.010000 | |
| iter = 1806, accuracy (cur) = 0.840000 (all), 0.848485 (pos), 0.823529 (neg) | |
| iter = 1806, accuracy (avg) = 0.854679 (all), 0.860286 (pos), 0.848328 (neg) | |
| data reader: epoch = 0, batch = 1807 / 4040 | |
| iter = 1807, cls_loss (cur) = 0.271667, cls_loss (avg) = 0.330669, lr = 0.010000 | |
| iter = 1807, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 1807, accuracy (avg) = 0.854532 (all), 0.860529 (pos), 0.847762 (neg) | |
| data reader: epoch = 0, batch = 1808 / 4040 | |
| iter = 1808, cls_loss (cur) = 0.315274, cls_loss (avg) = 0.330515, lr = 0.010000 | |
| iter = 1808, accuracy (cur) = 0.900000 (all), 0.862069 (pos), 0.952381 (neg) | |
| iter = 1808, accuracy (avg) = 0.854987 (all), 0.860545 (pos), 0.848808 (neg) | |
| data reader: epoch = 0, batch = 1809 / 4040 | |
| iter = 1809, cls_loss (cur) = 0.404584, cls_loss (avg) = 0.331256, lr = 0.010000 | |
| iter = 1809, accuracy (cur) = 0.780000 (all), 0.636364 (pos), 0.892857 (neg) | |
| iter = 1809, accuracy (avg) = 0.854237 (all), 0.858303 (pos), 0.849248 (neg) | |
| data reader: epoch = 0, batch = 1810 / 4040 | |
| iter = 1810, cls_loss (cur) = 0.370830, cls_loss (avg) = 0.331651, lr = 0.010000 | |
| iter = 1810, accuracy (cur) = 0.900000 (all), 0.904762 (pos), 0.896552 (neg) | |
| iter = 1810, accuracy (avg) = 0.854695 (all), 0.858767 (pos), 0.849721 (neg) | |
| data reader: epoch = 0, batch = 1811 / 4040 | |
| iter = 1811, cls_loss (cur) = 0.224109, cls_loss (avg) = 0.330576, lr = 0.010000 | |
| iter = 1811, accuracy (cur) = 0.880000 (all), 0.952381 (pos), 0.827586 (neg) | |
| iter = 1811, accuracy (avg) = 0.854948 (all), 0.859704 (pos), 0.849500 (neg) | |
| data reader: epoch = 0, batch = 1812 / 4040 | |
| iter = 1812, cls_loss (cur) = 0.329420, cls_loss (avg) = 0.330564, lr = 0.010000 | |
| iter = 1812, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 1812, accuracy (avg) = 0.854998 (all), 0.859625 (pos), 0.849701 (neg) | |
| data reader: epoch = 0, batch = 1813 / 4040 | |
| iter = 1813, cls_loss (cur) = 0.349761, cls_loss (avg) = 0.330756, lr = 0.010000 | |
| iter = 1813, accuracy (cur) = 0.840000 (all), 0.782609 (pos), 0.888889 (neg) | |
| iter = 1813, accuracy (avg) = 0.854848 (all), 0.858855 (pos), 0.850092 (neg) | |
| data reader: epoch = 0, batch = 1814 / 4040 | |
| iter = 1814, cls_loss (cur) = 0.247047, cls_loss (avg) = 0.329919, lr = 0.010000 | |
| iter = 1814, accuracy (cur) = 0.880000 (all), 0.827586 (pos), 0.952381 (neg) | |
| iter = 1814, accuracy (avg) = 0.855100 (all), 0.858542 (pos), 0.851115 (neg) | |
| data reader: epoch = 0, batch = 1815 / 4040 | |
| iter = 1815, cls_loss (cur) = 0.405059, cls_loss (avg) = 0.330671, lr = 0.010000 | |
| iter = 1815, accuracy (cur) = 0.800000 (all), 0.956522 (pos), 0.666667 (neg) | |
| iter = 1815, accuracy (avg) = 0.854549 (all), 0.859522 (pos), 0.849271 (neg) | |
| data reader: epoch = 0, batch = 1816 / 4040 | |
| iter = 1816, cls_loss (cur) = 0.397662, cls_loss (avg) = 0.331341, lr = 0.010000 | |
| iter = 1816, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.818182 (neg) | |
| iter = 1816, accuracy (avg) = 0.854403 (all), 0.859498 (pos), 0.848960 (neg) | |
| data reader: epoch = 0, batch = 1817 / 4040 | |
| iter = 1817, cls_loss (cur) = 0.349159, cls_loss (avg) = 0.331519, lr = 0.010000 | |
| iter = 1817, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.850000 (neg) | |
| iter = 1817, accuracy (avg) = 0.854259 (all), 0.859237 (pos), 0.848970 (neg) | |
| data reader: epoch = 0, batch = 1818 / 4040 | |
| iter = 1818, cls_loss (cur) = 0.350306, cls_loss (avg) = 0.331707, lr = 0.010000 | |
| iter = 1818, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1818, accuracy (avg) = 0.854317 (all), 0.859573 (pos), 0.848662 (neg) | |
| data reader: epoch = 0, batch = 1819 / 4040 | |
| iter = 1819, cls_loss (cur) = 0.397053, cls_loss (avg) = 0.332360, lr = 0.010000 | |
| iter = 1819, accuracy (cur) = 0.760000 (all), 0.904762 (pos), 0.655172 (neg) | |
| iter = 1819, accuracy (avg) = 0.853373 (all), 0.860025 (pos), 0.846728 (neg) | |
| data reader: epoch = 0, batch = 1820 / 4040 | |
| iter = 1820, cls_loss (cur) = 0.256441, cls_loss (avg) = 0.331601, lr = 0.010000 | |
| iter = 1820, accuracy (cur) = 0.900000 (all), 0.833333 (pos), 0.961538 (neg) | |
| iter = 1820, accuracy (avg) = 0.853840 (all), 0.859758 (pos), 0.847876 (neg) | |
| data reader: epoch = 0, batch = 1821 / 4040 | |
| iter = 1821, cls_loss (cur) = 0.367023, cls_loss (avg) = 0.331955, lr = 0.010000 | |
| iter = 1821, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 1821, accuracy (avg) = 0.853101 (all), 0.858938 (pos), 0.847223 (neg) | |
| data reader: epoch = 0, batch = 1822 / 4040 | |
| iter = 1822, cls_loss (cur) = 0.241069, cls_loss (avg) = 0.331046, lr = 0.010000 | |
| iter = 1822, accuracy (cur) = 0.920000 (all), 0.869565 (pos), 0.962963 (neg) | |
| iter = 1822, accuracy (avg) = 0.853770 (all), 0.859044 (pos), 0.848380 (neg) | |
| data reader: epoch = 0, batch = 1823 / 4040 | |
| iter = 1823, cls_loss (cur) = 0.273560, cls_loss (avg) = 0.330471, lr = 0.010000 | |
| iter = 1823, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 1823, accuracy (avg) = 0.854033 (all), 0.859654 (pos), 0.848297 (neg) | |
| data reader: epoch = 0, batch = 1824 / 4040 | |
| iter = 1824, cls_loss (cur) = 0.406927, cls_loss (avg) = 0.331236, lr = 0.010000 | |
| iter = 1824, accuracy (cur) = 0.840000 (all), 0.888889 (pos), 0.782609 (neg) | |
| iter = 1824, accuracy (avg) = 0.853892 (all), 0.859946 (pos), 0.847640 (neg) | |
| data reader: epoch = 0, batch = 1825 / 4040 | |
| iter = 1825, cls_loss (cur) = 0.280756, cls_loss (avg) = 0.330731, lr = 0.010000 | |
| iter = 1825, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.944444 (neg) | |
| iter = 1825, accuracy (avg) = 0.854353 (all), 0.860097 (pos), 0.848608 (neg) | |
| data reader: epoch = 0, batch = 1826 / 4040 | |
| iter = 1826, cls_loss (cur) = 0.345415, cls_loss (avg) = 0.330878, lr = 0.010000 | |
| iter = 1826, accuracy (cur) = 0.800000 (all), 0.785714 (pos), 0.818182 (neg) | |
| iter = 1826, accuracy (avg) = 0.853810 (all), 0.859353 (pos), 0.848304 (neg) | |
| data reader: epoch = 0, batch = 1827 / 4040 | |
| iter = 1827, cls_loss (cur) = 0.232861, cls_loss (avg) = 0.329898, lr = 0.010000 | |
| iter = 1827, accuracy (cur) = 0.920000 (all), 0.933333 (pos), 0.900000 (neg) | |
| iter = 1827, accuracy (avg) = 0.854472 (all), 0.860093 (pos), 0.848820 (neg) | |
| data reader: epoch = 0, batch = 1828 / 4040 | |
| iter = 1828, cls_loss (cur) = 0.323952, cls_loss (avg) = 0.329838, lr = 0.010000 | |
| iter = 1828, accuracy (cur) = 0.900000 (all), 0.913043 (pos), 0.888889 (neg) | |
| iter = 1828, accuracy (avg) = 0.854927 (all), 0.860622 (pos), 0.849221 (neg) | |
| data reader: epoch = 0, batch = 1829 / 4040 | |
| iter = 1829, cls_loss (cur) = 0.287596, cls_loss (avg) = 0.329416, lr = 0.010000 | |
| iter = 1829, accuracy (cur) = 0.860000 (all), 1.000000 (pos), 0.750000 (neg) | |
| iter = 1829, accuracy (avg) = 0.854978 (all), 0.862016 (pos), 0.848229 (neg) | |
| data reader: epoch = 0, batch = 1830 / 4040 | |
| iter = 1830, cls_loss (cur) = 0.258583, cls_loss (avg) = 0.328708, lr = 0.010000 | |
| iter = 1830, accuracy (cur) = 0.940000 (all), 0.958333 (pos), 0.923077 (neg) | |
| iter = 1830, accuracy (avg) = 0.855828 (all), 0.862979 (pos), 0.848977 (neg) | |
| data reader: epoch = 0, batch = 1831 / 4040 | |
| iter = 1831, cls_loss (cur) = 0.353514, cls_loss (avg) = 0.328956, lr = 0.010000 | |
| iter = 1831, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.857143 (neg) | |
| iter = 1831, accuracy (avg) = 0.855270 (all), 0.861622 (pos), 0.849059 (neg) | |
| data reader: epoch = 0, batch = 1832 / 4040 | |
| iter = 1832, cls_loss (cur) = 0.366705, cls_loss (avg) = 0.329333, lr = 0.010000 | |
| iter = 1832, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1832, accuracy (avg) = 0.855317 (all), 0.861806 (pos), 0.848968 (neg) | |
| data reader: epoch = 0, batch = 1833 / 4040 | |
| iter = 1833, cls_loss (cur) = 0.349628, cls_loss (avg) = 0.329536, lr = 0.010000 | |
| iter = 1833, accuracy (cur) = 0.820000 (all), 0.894737 (pos), 0.774194 (neg) | |
| iter = 1833, accuracy (avg) = 0.854964 (all), 0.862135 (pos), 0.848221 (neg) | |
| data reader: epoch = 0, batch = 1834 / 4040 | |
| iter = 1834, cls_loss (cur) = 0.327991, cls_loss (avg) = 0.329521, lr = 0.010000 | |
| iter = 1834, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1834, accuracy (avg) = 0.854614 (all), 0.861847 (pos), 0.847815 (neg) | |
| data reader: epoch = 0, batch = 1835 / 4040 | |
| iter = 1835, cls_loss (cur) = 0.297079, cls_loss (avg) = 0.329196, lr = 0.010000 | |
| iter = 1835, accuracy (cur) = 0.860000 (all), 0.750000 (pos), 0.961538 (neg) | |
| iter = 1835, accuracy (avg) = 0.854668 (all), 0.860729 (pos), 0.848953 (neg) | |
| data reader: epoch = 0, batch = 1836 / 4040 | |
| iter = 1836, cls_loss (cur) = 0.340635, cls_loss (avg) = 0.329311, lr = 0.010000 | |
| iter = 1836, accuracy (cur) = 0.860000 (all), 0.840000 (pos), 0.880000 (neg) | |
| iter = 1836, accuracy (avg) = 0.854721 (all), 0.860521 (pos), 0.849263 (neg) | |
| data reader: epoch = 0, batch = 1837 / 4040 | |
| iter = 1837, cls_loss (cur) = 0.681369, cls_loss (avg) = 0.332831, lr = 0.010000 | |
| iter = 1837, accuracy (cur) = 0.680000 (all), 0.677419 (pos), 0.684211 (neg) | |
| iter = 1837, accuracy (avg) = 0.852974 (all), 0.858690 (pos), 0.847613 (neg) | |
| data reader: epoch = 0, batch = 1838 / 4040 | |
| iter = 1838, cls_loss (cur) = 0.332374, cls_loss (avg) = 0.332827, lr = 0.010000 | |
| iter = 1838, accuracy (cur) = 0.860000 (all), 0.840000 (pos), 0.880000 (neg) | |
| iter = 1838, accuracy (avg) = 0.853044 (all), 0.858503 (pos), 0.847937 (neg) | |
| data reader: epoch = 0, batch = 1839 / 4040 | |
| iter = 1839, cls_loss (cur) = 0.339050, cls_loss (avg) = 0.332889, lr = 0.010000 | |
| iter = 1839, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 1839, accuracy (avg) = 0.852914 (all), 0.858437 (pos), 0.847718 (neg) | |
| data reader: epoch = 0, batch = 1840 / 4040 | |
| iter = 1840, cls_loss (cur) = 0.234608, cls_loss (avg) = 0.331906, lr = 0.010000 | |
| iter = 1840, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.818182 (neg) | |
| iter = 1840, accuracy (avg) = 0.853585 (all), 0.859853 (pos), 0.847423 (neg) | |
| data reader: epoch = 0, batch = 1841 / 4040 | |
| iter = 1841, cls_loss (cur) = 0.279735, cls_loss (avg) = 0.331384, lr = 0.010000 | |
| iter = 1841, accuracy (cur) = 0.880000 (all), 1.000000 (pos), 0.777778 (neg) | |
| iter = 1841, accuracy (avg) = 0.853849 (all), 0.861254 (pos), 0.846726 (neg) | |
| data reader: epoch = 0, batch = 1842 / 4040 | |
| iter = 1842, cls_loss (cur) = 0.435634, cls_loss (avg) = 0.332427, lr = 0.010000 | |
| iter = 1842, accuracy (cur) = 0.820000 (all), 0.739130 (pos), 0.888889 (neg) | |
| iter = 1842, accuracy (avg) = 0.853511 (all), 0.860033 (pos), 0.847148 (neg) | |
| data reader: epoch = 0, batch = 1843 / 4040 | |
| iter = 1843, cls_loss (cur) = 0.293583, cls_loss (avg) = 0.332038, lr = 0.010000 | |
| iter = 1843, accuracy (cur) = 0.840000 (all), 0.878788 (pos), 0.764706 (neg) | |
| iter = 1843, accuracy (avg) = 0.853375 (all), 0.860220 (pos), 0.846323 (neg) | |
| data reader: epoch = 0, batch = 1844 / 4040 | |
| iter = 1844, cls_loss (cur) = 0.460884, cls_loss (avg) = 0.333327, lr = 0.010000 | |
| iter = 1844, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 1844, accuracy (avg) = 0.853442 (all), 0.860547 (pos), 0.846042 (neg) | |
| data reader: epoch = 0, batch = 1845 / 4040 | |
| iter = 1845, cls_loss (cur) = 0.399079, cls_loss (avg) = 0.333984, lr = 0.010000 | |
| iter = 1845, accuracy (cur) = 0.740000 (all), 0.807692 (pos), 0.666667 (neg) | |
| iter = 1845, accuracy (avg) = 0.852307 (all), 0.860018 (pos), 0.844248 (neg) | |
| data reader: epoch = 0, batch = 1846 / 4040 | |
| iter = 1846, cls_loss (cur) = 0.383704, cls_loss (avg) = 0.334482, lr = 0.010000 | |
| iter = 1846, accuracy (cur) = 0.800000 (all), 0.851852 (pos), 0.739130 (neg) | |
| iter = 1846, accuracy (avg) = 0.851784 (all), 0.859936 (pos), 0.843197 (neg) | |
| data reader: epoch = 0, batch = 1847 / 4040 | |
| iter = 1847, cls_loss (cur) = 0.441953, cls_loss (avg) = 0.335556, lr = 0.010000 | |
| iter = 1847, accuracy (cur) = 0.820000 (all), 0.892857 (pos), 0.727273 (neg) | |
| iter = 1847, accuracy (avg) = 0.851466 (all), 0.860266 (pos), 0.842038 (neg) | |
| data reader: epoch = 0, batch = 1848 / 4040 | |
| iter = 1848, cls_loss (cur) = 0.267161, cls_loss (avg) = 0.334872, lr = 0.010000 | |
| iter = 1848, accuracy (cur) = 0.900000 (all), 0.964286 (pos), 0.818182 (neg) | |
| iter = 1848, accuracy (avg) = 0.851952 (all), 0.861306 (pos), 0.841799 (neg) | |
| data reader: epoch = 0, batch = 1849 / 4040 | |
| iter = 1849, cls_loss (cur) = 0.286726, cls_loss (avg) = 0.334391, lr = 0.010000 | |
| iter = 1849, accuracy (cur) = 0.880000 (all), 0.964286 (pos), 0.772727 (neg) | |
| iter = 1849, accuracy (avg) = 0.852232 (all), 0.862336 (pos), 0.841109 (neg) | |
| data reader: epoch = 0, batch = 1850 / 4040 | |
| iter = 1850, cls_loss (cur) = 0.445058, cls_loss (avg) = 0.335498, lr = 0.010000 | |
| iter = 1850, accuracy (cur) = 0.800000 (all), 0.888889 (pos), 0.750000 (neg) | |
| iter = 1850, accuracy (avg) = 0.851710 (all), 0.862601 (pos), 0.840197 (neg) | |
| data reader: epoch = 0, batch = 1851 / 4040 | |
| iter = 1851, cls_loss (cur) = 0.337533, cls_loss (avg) = 0.335518, lr = 0.010000 | |
| iter = 1851, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 1851, accuracy (avg) = 0.851593 (all), 0.861975 (pos), 0.840595 (neg) | |
| data reader: epoch = 0, batch = 1852 / 4040 | |
| iter = 1852, cls_loss (cur) = 0.336504, cls_loss (avg) = 0.335528, lr = 0.010000 | |
| iter = 1852, accuracy (cur) = 0.900000 (all), 0.950000 (pos), 0.866667 (neg) | |
| iter = 1852, accuracy (avg) = 0.852077 (all), 0.862855 (pos), 0.840856 (neg) | |
| data reader: epoch = 0, batch = 1853 / 4040 | |
| iter = 1853, cls_loss (cur) = 0.431587, cls_loss (avg) = 0.336488, lr = 0.010000 | |
| iter = 1853, accuracy (cur) = 0.760000 (all), 0.615385 (pos), 0.916667 (neg) | |
| iter = 1853, accuracy (avg) = 0.851156 (all), 0.860381 (pos), 0.841614 (neg) | |
| data reader: epoch = 0, batch = 1854 / 4040 | |
| iter = 1854, cls_loss (cur) = 0.381441, cls_loss (avg) = 0.336938, lr = 0.010000 | |
| iter = 1854, accuracy (cur) = 0.820000 (all), 0.720000 (pos), 0.920000 (neg) | |
| iter = 1854, accuracy (avg) = 0.850844 (all), 0.858977 (pos), 0.842398 (neg) | |
| data reader: epoch = 0, batch = 1855 / 4040 | |
| iter = 1855, cls_loss (cur) = 0.323575, cls_loss (avg) = 0.336804, lr = 0.010000 | |
| iter = 1855, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 1855, accuracy (avg) = 0.850936 (all), 0.859083 (pos), 0.842493 (neg) | |
| data reader: epoch = 0, batch = 1856 / 4040 | |
| iter = 1856, cls_loss (cur) = 0.297284, cls_loss (avg) = 0.336409, lr = 0.010000 | |
| iter = 1856, accuracy (cur) = 0.860000 (all), 0.791667 (pos), 0.923077 (neg) | |
| iter = 1856, accuracy (avg) = 0.851027 (all), 0.858409 (pos), 0.843299 (neg) | |
| data reader: epoch = 0, batch = 1857 / 4040 | |
| iter = 1857, cls_loss (cur) = 0.413021, cls_loss (avg) = 0.337175, lr = 0.010000 | |
| iter = 1857, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.812500 (neg) | |
| iter = 1857, accuracy (avg) = 0.850716 (all), 0.858158 (pos), 0.842991 (neg) | |
| data reader: epoch = 0, batch = 1858 / 4040 | |
| iter = 1858, cls_loss (cur) = 0.363873, cls_loss (avg) = 0.337442, lr = 0.010000 | |
| iter = 1858, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1858, accuracy (avg) = 0.850609 (all), 0.857653 (pos), 0.843311 (neg) | |
| data reader: epoch = 0, batch = 1859 / 4040 | |
| iter = 1859, cls_loss (cur) = 0.377389, cls_loss (avg) = 0.337842, lr = 0.010000 | |
| iter = 1859, accuracy (cur) = 0.820000 (all), 0.888889 (pos), 0.781250 (neg) | |
| iter = 1859, accuracy (avg) = 0.850303 (all), 0.857966 (pos), 0.842690 (neg) | |
| data reader: epoch = 0, batch = 1860 / 4040 | |
| iter = 1860, cls_loss (cur) = 0.417241, cls_loss (avg) = 0.338636, lr = 0.010000 | |
| iter = 1860, accuracy (cur) = 0.800000 (all), 0.733333 (pos), 0.900000 (neg) | |
| iter = 1860, accuracy (avg) = 0.849800 (all), 0.856719 (pos), 0.843263 (neg) | |
| data reader: epoch = 0, batch = 1861 / 4040 | |
| iter = 1861, cls_loss (cur) = 0.342376, cls_loss (avg) = 0.338673, lr = 0.010000 | |
| iter = 1861, accuracy (cur) = 0.820000 (all), 0.800000 (pos), 0.833333 (neg) | |
| iter = 1861, accuracy (avg) = 0.849502 (all), 0.856152 (pos), 0.843164 (neg) | |
| data reader: epoch = 0, batch = 1862 / 4040 | |
| iter = 1862, cls_loss (cur) = 0.248387, cls_loss (avg) = 0.337770, lr = 0.010000 | |
| iter = 1862, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 1862, accuracy (avg) = 0.849607 (all), 0.856052 (pos), 0.843482 (neg) | |
| data reader: epoch = 0, batch = 1863 / 4040 | |
| iter = 1863, cls_loss (cur) = 0.323815, cls_loss (avg) = 0.337631, lr = 0.010000 | |
| iter = 1863, accuracy (cur) = 0.880000 (all), 0.894737 (pos), 0.870968 (neg) | |
| iter = 1863, accuracy (avg) = 0.849911 (all), 0.856439 (pos), 0.843757 (neg) | |
| data reader: epoch = 0, batch = 1864 / 4040 | |
| iter = 1864, cls_loss (cur) = 0.221222, cls_loss (avg) = 0.336467, lr = 0.010000 | |
| iter = 1864, accuracy (cur) = 0.960000 (all), 0.923077 (pos), 1.000000 (neg) | |
| iter = 1864, accuracy (avg) = 0.851012 (all), 0.857105 (pos), 0.845319 (neg) | |
| data reader: epoch = 0, batch = 1865 / 4040 | |
| iter = 1865, cls_loss (cur) = 0.342826, cls_loss (avg) = 0.336530, lr = 0.010000 | |
| iter = 1865, accuracy (cur) = 0.840000 (all), 0.785714 (pos), 0.909091 (neg) | |
| iter = 1865, accuracy (avg) = 0.850902 (all), 0.856391 (pos), 0.845957 (neg) | |
| data reader: epoch = 0, batch = 1866 / 4040 | |
| iter = 1866, cls_loss (cur) = 0.230521, cls_loss (avg) = 0.335470, lr = 0.010000 | |
| iter = 1866, accuracy (cur) = 0.920000 (all), 0.892857 (pos), 0.954545 (neg) | |
| iter = 1866, accuracy (avg) = 0.851593 (all), 0.856756 (pos), 0.847043 (neg) | |
| data reader: epoch = 0, batch = 1867 / 4040 | |
| iter = 1867, cls_loss (cur) = 0.469334, cls_loss (avg) = 0.336809, lr = 0.010000 | |
| iter = 1867, accuracy (cur) = 0.800000 (all), 0.750000 (pos), 0.846154 (neg) | |
| iter = 1867, accuracy (avg) = 0.851077 (all), 0.855689 (pos), 0.847034 (neg) | |
| data reader: epoch = 0, batch = 1868 / 4040 | |
| iter = 1868, cls_loss (cur) = 0.283395, cls_loss (avg) = 0.336275, lr = 0.010000 | |
| iter = 1868, accuracy (cur) = 0.860000 (all), 0.909091 (pos), 0.821429 (neg) | |
| iter = 1868, accuracy (avg) = 0.851166 (all), 0.856223 (pos), 0.846778 (neg) | |
| data reader: epoch = 0, batch = 1869 / 4040 | |
| iter = 1869, cls_loss (cur) = 0.266161, cls_loss (avg) = 0.335573, lr = 0.010000 | |
| iter = 1869, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 1869, accuracy (avg) = 0.851654 (all), 0.856410 (pos), 0.847541 (neg) | |
| data reader: epoch = 0, batch = 1870 / 4040 | |
| iter = 1870, cls_loss (cur) = 0.362942, cls_loss (avg) = 0.335847, lr = 0.010000 | |
| iter = 1870, accuracy (cur) = 0.760000 (all), 0.806452 (pos), 0.684211 (neg) | |
| iter = 1870, accuracy (avg) = 0.850738 (all), 0.855911 (pos), 0.845908 (neg) | |
| data reader: epoch = 0, batch = 1871 / 4040 | |
| iter = 1871, cls_loss (cur) = 0.351606, cls_loss (avg) = 0.336005, lr = 0.010000 | |
| iter = 1871, accuracy (cur) = 0.840000 (all), 0.923077 (pos), 0.750000 (neg) | |
| iter = 1871, accuracy (avg) = 0.850630 (all), 0.856582 (pos), 0.844949 (neg) | |
| data reader: epoch = 0, batch = 1872 / 4040 | |
| iter = 1872, cls_loss (cur) = 0.268630, cls_loss (avg) = 0.335331, lr = 0.010000 | |
| iter = 1872, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 1872, accuracy (avg) = 0.851124 (all), 0.857107 (pos), 0.845428 (neg) | |
| data reader: epoch = 0, batch = 1873 / 4040 | |
| iter = 1873, cls_loss (cur) = 0.372128, cls_loss (avg) = 0.335699, lr = 0.010000 | |
| iter = 1873, accuracy (cur) = 0.840000 (all), 0.862069 (pos), 0.809524 (neg) | |
| iter = 1873, accuracy (avg) = 0.851013 (all), 0.857157 (pos), 0.845069 (neg) | |
| data reader: epoch = 0, batch = 1874 / 4040 | |
| iter = 1874, cls_loss (cur) = 0.240169, cls_loss (avg) = 0.334744, lr = 0.010000 | |
| iter = 1874, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 1874, accuracy (avg) = 0.851303 (all), 0.857716 (pos), 0.845137 (neg) | |
| data reader: epoch = 0, batch = 1875 / 4040 | |
| iter = 1875, cls_loss (cur) = 0.260457, cls_loss (avg) = 0.334001, lr = 0.010000 | |
| iter = 1875, accuracy (cur) = 0.940000 (all), 0.909091 (pos), 0.964286 (neg) | |
| iter = 1875, accuracy (avg) = 0.852190 (all), 0.858230 (pos), 0.846328 (neg) | |
| data reader: epoch = 0, batch = 1876 / 4040 | |
| iter = 1876, cls_loss (cur) = 0.310550, cls_loss (avg) = 0.333766, lr = 0.010000 | |
| iter = 1876, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.923077 (neg) | |
| iter = 1876, accuracy (avg) = 0.852068 (all), 0.857147 (pos), 0.847096 (neg) | |
| data reader: epoch = 0, batch = 1877 / 4040 | |
| iter = 1877, cls_loss (cur) = 0.364296, cls_loss (avg) = 0.334072, lr = 0.010000 | |
| iter = 1877, accuracy (cur) = 0.800000 (all), 0.842105 (pos), 0.774194 (neg) | |
| iter = 1877, accuracy (avg) = 0.851547 (all), 0.856997 (pos), 0.846367 (neg) | |
| data reader: epoch = 0, batch = 1878 / 4040 | |
| iter = 1878, cls_loss (cur) = 0.313946, cls_loss (avg) = 0.333870, lr = 0.010000 | |
| iter = 1878, accuracy (cur) = 0.840000 (all), 0.720000 (pos), 0.960000 (neg) | |
| iter = 1878, accuracy (avg) = 0.851432 (all), 0.855627 (pos), 0.847503 (neg) | |
| data reader: epoch = 0, batch = 1879 / 4040 | |
| iter = 1879, cls_loss (cur) = 0.259938, cls_loss (avg) = 0.333131, lr = 0.010000 | |
| iter = 1879, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 1879, accuracy (avg) = 0.851717 (all), 0.855871 (pos), 0.847828 (neg) | |
| data reader: epoch = 0, batch = 1880 / 4040 | |
| iter = 1880, cls_loss (cur) = 0.320805, cls_loss (avg) = 0.333008, lr = 0.010000 | |
| iter = 1880, accuracy (cur) = 0.860000 (all), 0.863636 (pos), 0.857143 (neg) | |
| iter = 1880, accuracy (avg) = 0.851800 (all), 0.855948 (pos), 0.847921 (neg) | |
| data reader: epoch = 0, batch = 1881 / 4040 | |
| iter = 1881, cls_loss (cur) = 0.347020, cls_loss (avg) = 0.333148, lr = 0.010000 | |
| iter = 1881, accuracy (cur) = 0.860000 (all), 0.861111 (pos), 0.857143 (neg) | |
| iter = 1881, accuracy (avg) = 0.851882 (all), 0.856000 (pos), 0.848013 (neg) | |
| data reader: epoch = 0, batch = 1882 / 4040 | |
| iter = 1882, cls_loss (cur) = 0.232086, cls_loss (avg) = 0.332137, lr = 0.010000 | |
| iter = 1882, accuracy (cur) = 0.900000 (all), 0.958333 (pos), 0.846154 (neg) | |
| iter = 1882, accuracy (avg) = 0.852363 (all), 0.857023 (pos), 0.847995 (neg) | |
| data reader: epoch = 0, batch = 1883 / 4040 | |
| iter = 1883, cls_loss (cur) = 0.504738, cls_loss (avg) = 0.333863, lr = 0.010000 | |
| iter = 1883, accuracy (cur) = 0.740000 (all), 0.884615 (pos), 0.583333 (neg) | |
| iter = 1883, accuracy (avg) = 0.851240 (all), 0.857299 (pos), 0.845348 (neg) | |
| data reader: epoch = 0, batch = 1884 / 4040 | |
| iter = 1884, cls_loss (cur) = 0.450758, cls_loss (avg) = 0.335032, lr = 0.010000 | |
| iter = 1884, accuracy (cur) = 0.780000 (all), 0.678571 (pos), 0.909091 (neg) | |
| iter = 1884, accuracy (avg) = 0.850527 (all), 0.855512 (pos), 0.845985 (neg) | |
| data reader: epoch = 0, batch = 1885 / 4040 | |
| iter = 1885, cls_loss (cur) = 0.272947, cls_loss (avg) = 0.334411, lr = 0.010000 | |
| iter = 1885, accuracy (cur) = 0.880000 (all), 0.920000 (pos), 0.840000 (neg) | |
| iter = 1885, accuracy (avg) = 0.850822 (all), 0.856157 (pos), 0.845926 (neg) | |
| data reader: epoch = 0, batch = 1886 / 4040 | |
| iter = 1886, cls_loss (cur) = 0.335606, cls_loss (avg) = 0.334423, lr = 0.010000 | |
| iter = 1886, accuracy (cur) = 0.820000 (all), 0.814815 (pos), 0.826087 (neg) | |
| iter = 1886, accuracy (avg) = 0.850514 (all), 0.855743 (pos), 0.845727 (neg) | |
| data reader: epoch = 0, batch = 1887 / 4040 | |
| iter = 1887, cls_loss (cur) = 0.385464, cls_loss (avg) = 0.334934, lr = 0.010000 | |
| iter = 1887, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1887, accuracy (avg) = 0.850209 (all), 0.855519 (pos), 0.845347 (neg) | |
| data reader: epoch = 0, batch = 1888 / 4040 | |
| iter = 1888, cls_loss (cur) = 0.205293, cls_loss (avg) = 0.333637, lr = 0.010000 | |
| iter = 1888, accuracy (cur) = 0.940000 (all), 0.923077 (pos), 0.958333 (neg) | |
| iter = 1888, accuracy (avg) = 0.851107 (all), 0.856195 (pos), 0.846477 (neg) | |
| data reader: epoch = 0, batch = 1889 / 4040 | |
| iter = 1889, cls_loss (cur) = 0.215096, cls_loss (avg) = 0.332452, lr = 0.010000 | |
| iter = 1889, accuracy (cur) = 0.900000 (all), 0.960000 (pos), 0.840000 (neg) | |
| iter = 1889, accuracy (avg) = 0.851596 (all), 0.857233 (pos), 0.846412 (neg) | |
| data reader: epoch = 0, batch = 1890 / 4040 | |
| iter = 1890, cls_loss (cur) = 0.337914, cls_loss (avg) = 0.332507, lr = 0.010000 | |
| iter = 1890, accuracy (cur) = 0.780000 (all), 0.750000 (pos), 0.818182 (neg) | |
| iter = 1890, accuracy (avg) = 0.850880 (all), 0.856161 (pos), 0.846130 (neg) | |
| data reader: epoch = 0, batch = 1891 / 4040 | |
| iter = 1891, cls_loss (cur) = 0.381017, cls_loss (avg) = 0.332992, lr = 0.010000 | |
| iter = 1891, accuracy (cur) = 0.780000 (all), 0.923077 (pos), 0.625000 (neg) | |
| iter = 1891, accuracy (avg) = 0.850171 (all), 0.856830 (pos), 0.843918 (neg) | |
| data reader: epoch = 0, batch = 1892 / 4040 | |
| iter = 1892, cls_loss (cur) = 0.329655, cls_loss (avg) = 0.332958, lr = 0.010000 | |
| iter = 1892, accuracy (cur) = 0.840000 (all), 0.952381 (pos), 0.758621 (neg) | |
| iter = 1892, accuracy (avg) = 0.850069 (all), 0.857785 (pos), 0.843065 (neg) | |
| data reader: epoch = 0, batch = 1893 / 4040 | |
| iter = 1893, cls_loss (cur) = 0.303322, cls_loss (avg) = 0.332662, lr = 0.010000 | |
| iter = 1893, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 1893, accuracy (avg) = 0.850368 (all), 0.858007 (pos), 0.843435 (neg) | |
| data reader: epoch = 0, batch = 1894 / 4040 | |
| iter = 1894, cls_loss (cur) = 0.321258, cls_loss (avg) = 0.332548, lr = 0.010000 | |
| iter = 1894, accuracy (cur) = 0.820000 (all), 0.826087 (pos), 0.814815 (neg) | |
| iter = 1894, accuracy (avg) = 0.850065 (all), 0.857688 (pos), 0.843149 (neg) | |
| data reader: epoch = 0, batch = 1895 / 4040 | |
| iter = 1895, cls_loss (cur) = 0.272410, cls_loss (avg) = 0.331946, lr = 0.010000 | |
| iter = 1895, accuracy (cur) = 0.900000 (all), 0.903226 (pos), 0.894737 (neg) | |
| iter = 1895, accuracy (avg) = 0.850564 (all), 0.858144 (pos), 0.843664 (neg) | |
| data reader: epoch = 0, batch = 1896 / 4040 | |
| iter = 1896, cls_loss (cur) = 0.277241, cls_loss (avg) = 0.331399, lr = 0.010000 | |
| iter = 1896, accuracy (cur) = 0.840000 (all), 0.722222 (pos), 0.906250 (neg) | |
| iter = 1896, accuracy (avg) = 0.850458 (all), 0.856784 (pos), 0.844290 (neg) | |
| data reader: epoch = 0, batch = 1897 / 4040 | |
| iter = 1897, cls_loss (cur) = 0.344863, cls_loss (avg) = 0.331534, lr = 0.010000 | |
| iter = 1897, accuracy (cur) = 0.820000 (all), 0.689655 (pos), 1.000000 (neg) | |
| iter = 1897, accuracy (avg) = 0.850154 (all), 0.855113 (pos), 0.845847 (neg) | |
| data reader: epoch = 0, batch = 1898 / 4040 | |
| iter = 1898, cls_loss (cur) = 0.469095, cls_loss (avg) = 0.332910, lr = 0.010000 | |
| iter = 1898, accuracy (cur) = 0.740000 (all), 0.772727 (pos), 0.714286 (neg) | |
| iter = 1898, accuracy (avg) = 0.849052 (all), 0.854289 (pos), 0.844532 (neg) | |
| data reader: epoch = 0, batch = 1899 / 4040 | |
| iter = 1899, cls_loss (cur) = 0.222970, cls_loss (avg) = 0.331810, lr = 0.010000 | |
| iter = 1899, accuracy (cur) = 0.880000 (all), 0.769231 (pos), 1.000000 (neg) | |
| iter = 1899, accuracy (avg) = 0.849362 (all), 0.853439 (pos), 0.846086 (neg) | |
| data reader: epoch = 0, batch = 1900 / 4040 | |
| iter = 1900, cls_loss (cur) = 0.391058, cls_loss (avg) = 0.332403, lr = 0.010000 | |
| iter = 1900, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.909091 (neg) | |
| iter = 1900, accuracy (avg) = 0.849068 (all), 0.852404 (pos), 0.846716 (neg) | |
| data reader: epoch = 0, batch = 1901 / 4040 | |
| iter = 1901, cls_loss (cur) = 0.421172, cls_loss (avg) = 0.333290, lr = 0.010000 | |
| iter = 1901, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.760000 (neg) | |
| iter = 1901, accuracy (avg) = 0.848378 (all), 0.851880 (pos), 0.845849 (neg) | |
| data reader: epoch = 0, batch = 1902 / 4040 | |
| iter = 1902, cls_loss (cur) = 0.336415, cls_loss (avg) = 0.333322, lr = 0.010000 | |
| iter = 1902, accuracy (cur) = 0.840000 (all), 0.903226 (pos), 0.736842 (neg) | |
| iter = 1902, accuracy (avg) = 0.848294 (all), 0.852394 (pos), 0.844759 (neg) | |
| data reader: epoch = 0, batch = 1903 / 4040 | |
| iter = 1903, cls_loss (cur) = 0.294483, cls_loss (avg) = 0.332933, lr = 0.010000 | |
| iter = 1903, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 1903, accuracy (avg) = 0.848411 (all), 0.852331 (pos), 0.845062 (neg) | |
| data reader: epoch = 0, batch = 1904 / 4040 | |
| iter = 1904, cls_loss (cur) = 0.301381, cls_loss (avg) = 0.332618, lr = 0.010000 | |
| iter = 1904, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 1904, accuracy (avg) = 0.848527 (all), 0.852327 (pos), 0.845307 (neg) | |
| data reader: epoch = 0, batch = 1905 / 4040 | |
| iter = 1905, cls_loss (cur) = 0.458195, cls_loss (avg) = 0.333874, lr = 0.010000 | |
| iter = 1905, accuracy (cur) = 0.720000 (all), 0.800000 (pos), 0.600000 (neg) | |
| iter = 1905, accuracy (avg) = 0.847241 (all), 0.851803 (pos), 0.842854 (neg) | |
| data reader: epoch = 0, batch = 1906 / 4040 | |
| iter = 1906, cls_loss (cur) = 0.242007, cls_loss (avg) = 0.332955, lr = 0.010000 | |
| iter = 1906, accuracy (cur) = 0.920000 (all), 0.961538 (pos), 0.875000 (neg) | |
| iter = 1906, accuracy (avg) = 0.847969 (all), 0.852901 (pos), 0.843175 (neg) | |
| data reader: epoch = 0, batch = 1907 / 4040 | |
| iter = 1907, cls_loss (cur) = 0.259414, cls_loss (avg) = 0.332219, lr = 0.010000 | |
| iter = 1907, accuracy (cur) = 0.920000 (all), 0.900000 (pos), 0.933333 (neg) | |
| iter = 1907, accuracy (avg) = 0.848689 (all), 0.853372 (pos), 0.844077 (neg) | |
| data reader: epoch = 0, batch = 1908 / 4040 | |
| iter = 1908, cls_loss (cur) = 0.321231, cls_loss (avg) = 0.332110, lr = 0.010000 | |
| iter = 1908, accuracy (cur) = 0.820000 (all), 0.928571 (pos), 0.681818 (neg) | |
| iter = 1908, accuracy (avg) = 0.848402 (all), 0.854124 (pos), 0.842454 (neg) | |
| data reader: epoch = 0, batch = 1909 / 4040 | |
| iter = 1909, cls_loss (cur) = 0.342893, cls_loss (avg) = 0.332217, lr = 0.010000 | |
| iter = 1909, accuracy (cur) = 0.820000 (all), 0.714286 (pos), 0.954545 (neg) | |
| iter = 1909, accuracy (avg) = 0.848118 (all), 0.852725 (pos), 0.843575 (neg) | |
| data reader: epoch = 0, batch = 1910 / 4040 | |
| iter = 1910, cls_loss (cur) = 0.444068, cls_loss (avg) = 0.333336, lr = 0.010000 | |
| iter = 1910, accuracy (cur) = 0.720000 (all), 0.818182 (pos), 0.642857 (neg) | |
| iter = 1910, accuracy (avg) = 0.846837 (all), 0.852380 (pos), 0.841568 (neg) | |
| data reader: epoch = 0, batch = 1911 / 4040 | |
| iter = 1911, cls_loss (cur) = 0.340471, cls_loss (avg) = 0.333407, lr = 0.010000 | |
| iter = 1911, accuracy (cur) = 0.820000 (all), 0.909091 (pos), 0.750000 (neg) | |
| iter = 1911, accuracy (avg) = 0.846569 (all), 0.852947 (pos), 0.840652 (neg) | |
| data reader: epoch = 0, batch = 1912 / 4040 | |
| iter = 1912, cls_loss (cur) = 0.495784, cls_loss (avg) = 0.335031, lr = 0.010000 | |
| iter = 1912, accuracy (cur) = 0.780000 (all), 0.724138 (pos), 0.857143 (neg) | |
| iter = 1912, accuracy (avg) = 0.845903 (all), 0.851659 (pos), 0.840817 (neg) | |
| data reader: epoch = 0, batch = 1913 / 4040 | |
| iter = 1913, cls_loss (cur) = 0.190095, cls_loss (avg) = 0.333582, lr = 0.010000 | |
| iter = 1913, accuracy (cur) = 0.980000 (all), 0.968750 (pos), 1.000000 (neg) | |
| iter = 1913, accuracy (avg) = 0.847244 (all), 0.852830 (pos), 0.842409 (neg) | |
| data reader: epoch = 0, batch = 1914 / 4040 | |
| iter = 1914, cls_loss (cur) = 0.308035, cls_loss (avg) = 0.333326, lr = 0.010000 | |
| iter = 1914, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 1914, accuracy (avg) = 0.847572 (all), 0.852562 (pos), 0.843244 (neg) | |
| data reader: epoch = 0, batch = 1915 / 4040 | |
| iter = 1915, cls_loss (cur) = 0.261956, cls_loss (avg) = 0.332613, lr = 0.010000 | |
| iter = 1915, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 1915, accuracy (avg) = 0.848096 (all), 0.852498 (pos), 0.844395 (neg) | |
| data reader: epoch = 0, batch = 1916 / 4040 | |
| iter = 1916, cls_loss (cur) = 0.349052, cls_loss (avg) = 0.332777, lr = 0.010000 | |
| iter = 1916, accuracy (cur) = 0.780000 (all), 0.739130 (pos), 0.814815 (neg) | |
| iter = 1916, accuracy (avg) = 0.847415 (all), 0.851365 (pos), 0.844099 (neg) | |
| data reader: epoch = 0, batch = 1917 / 4040 | |
| iter = 1917, cls_loss (cur) = 0.334561, cls_loss (avg) = 0.332795, lr = 0.010000 | |
| iter = 1917, accuracy (cur) = 0.820000 (all), 0.875000 (pos), 0.722222 (neg) | |
| iter = 1917, accuracy (avg) = 0.847141 (all), 0.851601 (pos), 0.842880 (neg) | |
| data reader: epoch = 0, batch = 1918 / 4040 | |
| iter = 1918, cls_loss (cur) = 0.332080, cls_loss (avg) = 0.332788, lr = 0.010000 | |
| iter = 1918, accuracy (cur) = 0.860000 (all), 0.869565 (pos), 0.851852 (neg) | |
| iter = 1918, accuracy (avg) = 0.847269 (all), 0.851781 (pos), 0.842970 (neg) | |
| data reader: epoch = 0, batch = 1919 / 4040 | |
| iter = 1919, cls_loss (cur) = 0.273750, cls_loss (avg) = 0.332197, lr = 0.010000 | |
| iter = 1919, accuracy (cur) = 0.880000 (all), 0.960000 (pos), 0.800000 (neg) | |
| iter = 1919, accuracy (avg) = 0.847597 (all), 0.852863 (pos), 0.842540 (neg) | |
| data reader: epoch = 0, batch = 1920 / 4040 | |
| iter = 1920, cls_loss (cur) = 0.329416, cls_loss (avg) = 0.332169, lr = 0.010000 | |
| iter = 1920, accuracy (cur) = 0.860000 (all), 0.952381 (pos), 0.793103 (neg) | |
| iter = 1920, accuracy (avg) = 0.847721 (all), 0.853858 (pos), 0.842046 (neg) | |
| data reader: epoch = 0, batch = 1921 / 4040 | |
| iter = 1921, cls_loss (cur) = 0.225468, cls_loss (avg) = 0.331102, lr = 0.010000 | |
| iter = 1921, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 1921, accuracy (avg) = 0.848244 (all), 0.854319 (pos), 0.842626 (neg) | |
| data reader: epoch = 0, batch = 1922 / 4040 | |
| iter = 1922, cls_loss (cur) = 0.337830, cls_loss (avg) = 0.331170, lr = 0.010000 | |
| iter = 1922, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 1922, accuracy (avg) = 0.847961 (all), 0.854109 (pos), 0.842276 (neg) | |
| data reader: epoch = 0, batch = 1923 / 4040 | |
| iter = 1923, cls_loss (cur) = 0.299893, cls_loss (avg) = 0.330857, lr = 0.010000 | |
| iter = 1923, accuracy (cur) = 0.840000 (all), 0.789474 (pos), 0.870968 (neg) | |
| iter = 1923, accuracy (avg) = 0.847882 (all), 0.853463 (pos), 0.842563 (neg) | |
| data reader: epoch = 0, batch = 1924 / 4040 | |
| iter = 1924, cls_loss (cur) = 0.346626, cls_loss (avg) = 0.331015, lr = 0.010000 | |
| iter = 1924, accuracy (cur) = 0.800000 (all), 0.880000 (pos), 0.720000 (neg) | |
| iter = 1924, accuracy (avg) = 0.847403 (all), 0.853728 (pos), 0.841338 (neg) | |
| data reader: epoch = 0, batch = 1925 / 4040 | |
| iter = 1925, cls_loss (cur) = 0.303790, cls_loss (avg) = 0.330742, lr = 0.010000 | |
| iter = 1925, accuracy (cur) = 0.840000 (all), 0.846154 (pos), 0.833333 (neg) | |
| iter = 1925, accuracy (avg) = 0.847329 (all), 0.853653 (pos), 0.841257 (neg) | |
| data reader: epoch = 0, batch = 1926 / 4040 | |
| iter = 1926, cls_loss (cur) = 0.251358, cls_loss (avg) = 0.329949, lr = 0.010000 | |
| iter = 1926, accuracy (cur) = 0.900000 (all), 0.928571 (pos), 0.863636 (neg) | |
| iter = 1926, accuracy (avg) = 0.847855 (all), 0.854402 (pos), 0.841481 (neg) | |
| data reader: epoch = 0, batch = 1927 / 4040 | |
| iter = 1927, cls_loss (cur) = 0.328944, cls_loss (avg) = 0.329938, lr = 0.010000 | |
| iter = 1927, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 1927, accuracy (avg) = 0.848377 (all), 0.855058 (pos), 0.841866 (neg) | |
| data reader: epoch = 0, batch = 1928 / 4040 | |
| iter = 1928, cls_loss (cur) = 0.333224, cls_loss (avg) = 0.329971, lr = 0.010000 | |
| iter = 1928, accuracy (cur) = 0.840000 (all), 0.866667 (pos), 0.800000 (neg) | |
| iter = 1928, accuracy (avg) = 0.848293 (all), 0.855174 (pos), 0.841448 (neg) | |
| data reader: epoch = 0, batch = 1929 / 4040 | |
| iter = 1929, cls_loss (cur) = 0.298651, cls_loss (avg) = 0.329658, lr = 0.010000 | |
| iter = 1929, accuracy (cur) = 0.860000 (all), 0.850000 (pos), 0.866667 (neg) | |
| iter = 1929, accuracy (avg) = 0.848410 (all), 0.855122 (pos), 0.841700 (neg) | |
| data reader: epoch = 0, batch = 1930 / 4040 | |
| iter = 1930, cls_loss (cur) = 0.416041, cls_loss (avg) = 0.330522, lr = 0.010000 | |
| iter = 1930, accuracy (cur) = 0.800000 (all), 0.708333 (pos), 0.884615 (neg) | |
| iter = 1930, accuracy (avg) = 0.847926 (all), 0.853654 (pos), 0.842129 (neg) | |
| data reader: epoch = 0, batch = 1931 / 4040 | |
| iter = 1931, cls_loss (cur) = 0.353727, cls_loss (avg) = 0.330754, lr = 0.010000 | |
| iter = 1931, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.862069 (neg) | |
| iter = 1931, accuracy (avg) = 0.848047 (all), 0.853689 (pos), 0.842329 (neg) | |
| data reader: epoch = 0, batch = 1932 / 4040 | |
| iter = 1932, cls_loss (cur) = 0.341242, cls_loss (avg) = 0.330859, lr = 0.010000 | |
| iter = 1932, accuracy (cur) = 0.800000 (all), 0.727273 (pos), 0.857143 (neg) | |
| iter = 1932, accuracy (avg) = 0.847566 (all), 0.852425 (pos), 0.842477 (neg) | |
| data reader: epoch = 0, batch = 1933 / 4040 | |
| iter = 1933, cls_loss (cur) = 0.332815, cls_loss (avg) = 0.330878, lr = 0.010000 | |
| iter = 1933, accuracy (cur) = 0.820000 (all), 0.850000 (pos), 0.800000 (neg) | |
| iter = 1933, accuracy (avg) = 0.847291 (all), 0.852401 (pos), 0.842052 (neg) | |
| data reader: epoch = 0, batch = 1934 / 4040 | |
| iter = 1934, cls_loss (cur) = 0.316925, cls_loss (avg) = 0.330739, lr = 0.010000 | |
| iter = 1934, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 1934, accuracy (avg) = 0.847018 (all), 0.851703 (pos), 0.842150 (neg) | |
| data reader: epoch = 0, batch = 1935 / 4040 | |
| iter = 1935, cls_loss (cur) = 0.274743, cls_loss (avg) = 0.330179, lr = 0.010000 | |
| iter = 1935, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 1935, accuracy (avg) = 0.847548 (all), 0.852386 (pos), 0.842528 (neg) | |
| data reader: epoch = 0, batch = 1936 / 4040 | |
| iter = 1936, cls_loss (cur) = 0.221551, cls_loss (avg) = 0.329093, lr = 0.010000 | |
| iter = 1936, accuracy (cur) = 0.980000 (all), 0.965517 (pos), 1.000000 (neg) | |
| iter = 1936, accuracy (avg) = 0.848872 (all), 0.853517 (pos), 0.844103 (neg) | |
| data reader: epoch = 0, batch = 1937 / 4040 | |
| iter = 1937, cls_loss (cur) = 0.342255, cls_loss (avg) = 0.329224, lr = 0.010000 | |
| iter = 1937, accuracy (cur) = 0.860000 (all), 0.821429 (pos), 0.909091 (neg) | |
| iter = 1937, accuracy (avg) = 0.848983 (all), 0.853196 (pos), 0.844753 (neg) | |
| data reader: epoch = 0, batch = 1938 / 4040 | |
| iter = 1938, cls_loss (cur) = 0.287237, cls_loss (avg) = 0.328804, lr = 0.010000 | |
| iter = 1938, accuracy (cur) = 0.880000 (all), 0.916667 (pos), 0.846154 (neg) | |
| iter = 1938, accuracy (avg) = 0.849294 (all), 0.853831 (pos), 0.844767 (neg) | |
| data reader: epoch = 0, batch = 1939 / 4040 | |
| iter = 1939, cls_loss (cur) = 0.336858, cls_loss (avg) = 0.328885, lr = 0.010000 | |
| iter = 1939, accuracy (cur) = 0.880000 (all), 0.782609 (pos), 0.962963 (neg) | |
| iter = 1939, accuracy (avg) = 0.849601 (all), 0.853119 (pos), 0.845949 (neg) | |
| data reader: epoch = 0, batch = 1940 / 4040 | |
| iter = 1940, cls_loss (cur) = 0.265895, cls_loss (avg) = 0.328255, lr = 0.010000 | |
| iter = 1940, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.931034 (neg) | |
| iter = 1940, accuracy (avg) = 0.850105 (all), 0.853159 (pos), 0.846800 (neg) | |
| data reader: epoch = 0, batch = 1941 / 4040 | |
| iter = 1941, cls_loss (cur) = 0.334588, cls_loss (avg) = 0.328318, lr = 0.010000 | |
| iter = 1941, accuracy (cur) = 0.840000 (all), 0.807692 (pos), 0.875000 (neg) | |
| iter = 1941, accuracy (avg) = 0.850004 (all), 0.852704 (pos), 0.847082 (neg) | |
| data reader: epoch = 0, batch = 1942 / 4040 | |
| iter = 1942, cls_loss (cur) = 0.294548, cls_loss (avg) = 0.327981, lr = 0.010000 | |
| iter = 1942, accuracy (cur) = 0.780000 (all), 0.720000 (pos), 0.840000 (neg) | |
| iter = 1942, accuracy (avg) = 0.849304 (all), 0.851377 (pos), 0.847011 (neg) | |
| data reader: epoch = 0, batch = 1943 / 4040 | |
| iter = 1943, cls_loss (cur) = 0.265238, cls_loss (avg) = 0.327353, lr = 0.010000 | |
| iter = 1943, accuracy (cur) = 0.920000 (all), 0.956522 (pos), 0.888889 (neg) | |
| iter = 1943, accuracy (avg) = 0.850010 (all), 0.852429 (pos), 0.847430 (neg) | |
| data reader: epoch = 0, batch = 1944 / 4040 | |
| iter = 1944, cls_loss (cur) = 0.320180, cls_loss (avg) = 0.327282, lr = 0.010000 | |
| iter = 1944, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 1944, accuracy (avg) = 0.850110 (all), 0.852525 (pos), 0.847527 (neg) | |
| data reader: epoch = 0, batch = 1945 / 4040 | |
| iter = 1945, cls_loss (cur) = 0.296154, cls_loss (avg) = 0.326970, lr = 0.010000 | |
| iter = 1945, accuracy (cur) = 0.880000 (all), 0.870968 (pos), 0.894737 (neg) | |
| iter = 1945, accuracy (avg) = 0.850409 (all), 0.852710 (pos), 0.847999 (neg) | |
| data reader: epoch = 0, batch = 1946 / 4040 | |
| iter = 1946, cls_loss (cur) = 0.299013, cls_loss (avg) = 0.326691, lr = 0.010000 | |
| iter = 1946, accuracy (cur) = 0.900000 (all), 0.892857 (pos), 0.909091 (neg) | |
| iter = 1946, accuracy (avg) = 0.850905 (all), 0.853111 (pos), 0.848610 (neg) | |
| data reader: epoch = 0, batch = 1947 / 4040 | |
| iter = 1947, cls_loss (cur) = 0.378301, cls_loss (avg) = 0.327207, lr = 0.010000 | |
| iter = 1947, accuracy (cur) = 0.860000 (all), 0.954545 (pos), 0.785714 (neg) | |
| iter = 1947, accuracy (avg) = 0.850996 (all), 0.854125 (pos), 0.847981 (neg) | |
| data reader: epoch = 0, batch = 1948 / 4040 | |
| iter = 1948, cls_loss (cur) = 0.295026, cls_loss (avg) = 0.326885, lr = 0.010000 | |
| iter = 1948, accuracy (cur) = 0.860000 (all), 0.866667 (pos), 0.850000 (neg) | |
| iter = 1948, accuracy (avg) = 0.851086 (all), 0.854251 (pos), 0.848001 (neg) | |
| data reader: epoch = 0, batch = 1949 / 4040 | |
| iter = 1949, cls_loss (cur) = 0.384900, cls_loss (avg) = 0.327465, lr = 0.010000 | |
| iter = 1949, accuracy (cur) = 0.800000 (all), 0.826087 (pos), 0.777778 (neg) | |
| iter = 1949, accuracy (avg) = 0.850575 (all), 0.853969 (pos), 0.847299 (neg) | |
| data reader: epoch = 0, batch = 1950 / 4040 | |
| iter = 1950, cls_loss (cur) = 0.377926, cls_loss (avg) = 0.327970, lr = 0.010000 | |
| iter = 1950, accuracy (cur) = 0.820000 (all), 0.851852 (pos), 0.782609 (neg) | |
| iter = 1950, accuracy (avg) = 0.850270 (all), 0.853948 (pos), 0.846652 (neg) | |
| data reader: epoch = 0, batch = 1951 / 4040 | |
| iter = 1951, cls_loss (cur) = 0.257170, cls_loss (avg) = 0.327262, lr = 0.010000 | |
| iter = 1951, accuracy (cur) = 0.880000 (all), 0.863636 (pos), 0.892857 (neg) | |
| iter = 1951, accuracy (avg) = 0.850567 (all), 0.854045 (pos), 0.847114 (neg) | |
| data reader: epoch = 0, batch = 1952 / 4040 | |
| iter = 1952, cls_loss (cur) = 0.306118, cls_loss (avg) = 0.327050, lr = 0.010000 | |
| iter = 1952, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 1952, accuracy (avg) = 0.850861 (all), 0.853765 (pos), 0.847902 (neg) | |
| data reader: epoch = 0, batch = 1953 / 4040 | |
| iter = 1953, cls_loss (cur) = 0.296592, cls_loss (avg) = 0.326746, lr = 0.010000 | |
| iter = 1953, accuracy (cur) = 0.860000 (all), 0.952381 (pos), 0.793103 (neg) | |
| iter = 1953, accuracy (avg) = 0.850953 (all), 0.854751 (pos), 0.847354 (neg) | |
| data reader: epoch = 0, batch = 1954 / 4040 | |
| iter = 1954, cls_loss (cur) = 0.299411, cls_loss (avg) = 0.326472, lr = 0.010000 | |
| iter = 1954, accuracy (cur) = 0.940000 (all), 0.925926 (pos), 0.956522 (neg) | |
| iter = 1954, accuracy (avg) = 0.851843 (all), 0.855463 (pos), 0.848446 (neg) | |
| data reader: epoch = 0, batch = 1955 / 4040 | |
| iter = 1955, cls_loss (cur) = 0.422396, cls_loss (avg) = 0.327432, lr = 0.010000 | |
| iter = 1955, accuracy (cur) = 0.780000 (all), 0.793103 (pos), 0.761905 (neg) | |
| iter = 1955, accuracy (avg) = 0.851125 (all), 0.854840 (pos), 0.847580 (neg) | |
| data reader: epoch = 0, batch = 1956 / 4040 | |
| iter = 1956, cls_loss (cur) = 0.300638, cls_loss (avg) = 0.327164, lr = 0.010000 | |
| iter = 1956, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 1956, accuracy (avg) = 0.851413 (all), 0.855180 (pos), 0.847800 (neg) | |
| data reader: epoch = 0, batch = 1957 / 4040 | |
| iter = 1957, cls_loss (cur) = 0.386916, cls_loss (avg) = 0.327761, lr = 0.010000 | |
| iter = 1957, accuracy (cur) = 0.800000 (all), 0.851852 (pos), 0.739130 (neg) | |
| iter = 1957, accuracy (avg) = 0.850899 (all), 0.855147 (pos), 0.846714 (neg) | |
| data reader: epoch = 0, batch = 1958 / 4040 | |
| iter = 1958, cls_loss (cur) = 0.299161, cls_loss (avg) = 0.327475, lr = 0.010000 | |
| iter = 1958, accuracy (cur) = 0.880000 (all), 0.931034 (pos), 0.809524 (neg) | |
| iter = 1958, accuracy (avg) = 0.851190 (all), 0.855906 (pos), 0.846342 (neg) | |
| data reader: epoch = 0, batch = 1959 / 4040 | |
| iter = 1959, cls_loss (cur) = 0.219881, cls_loss (avg) = 0.326399, lr = 0.010000 | |
| iter = 1959, accuracy (cur) = 0.900000 (all), 0.840000 (pos), 0.960000 (neg) | |
| iter = 1959, accuracy (avg) = 0.851678 (all), 0.855747 (pos), 0.847478 (neg) | |
| data reader: epoch = 0, batch = 1960 / 4040 | |
| iter = 1960, cls_loss (cur) = 0.287320, cls_loss (avg) = 0.326008, lr = 0.010000 | |
| iter = 1960, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 1960, accuracy (avg) = 0.851762 (all), 0.856389 (pos), 0.847004 (neg) | |
| data reader: epoch = 0, batch = 1961 / 4040 | |
| iter = 1961, cls_loss (cur) = 0.322086, cls_loss (avg) = 0.325969, lr = 0.010000 | |
| iter = 1961, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 1961, accuracy (avg) = 0.852244 (all), 0.856714 (pos), 0.847664 (neg) | |
| data reader: epoch = 0, batch = 1962 / 4040 | |
| iter = 1962, cls_loss (cur) = 0.220334, cls_loss (avg) = 0.324913, lr = 0.010000 | |
| iter = 1962, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 1962, accuracy (avg) = 0.852722 (all), 0.857314 (pos), 0.848033 (neg) | |
| data reader: epoch = 0, batch = 1963 / 4040 | |
| iter = 1963, cls_loss (cur) = 0.266660, cls_loss (avg) = 0.324330, lr = 0.010000 | |
| iter = 1963, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 1963, accuracy (avg) = 0.852794 (all), 0.857541 (pos), 0.847953 (neg) | |
| data reader: epoch = 0, batch = 1964 / 4040 | |
| iter = 1964, cls_loss (cur) = 0.262681, cls_loss (avg) = 0.323714, lr = 0.010000 | |
| iter = 1964, accuracy (cur) = 0.880000 (all), 0.880000 (pos), 0.880000 (neg) | |
| iter = 1964, accuracy (avg) = 0.853066 (all), 0.857765 (pos), 0.848274 (neg) | |
| data reader: epoch = 0, batch = 1965 / 4040 | |
| iter = 1965, cls_loss (cur) = 0.316228, cls_loss (avg) = 0.323639, lr = 0.010000 | |
| iter = 1965, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 1965, accuracy (avg) = 0.853136 (all), 0.857938 (pos), 0.848252 (neg) | |
| data reader: epoch = 0, batch = 1966 / 4040 | |
| iter = 1966, cls_loss (cur) = 0.406168, cls_loss (avg) = 0.324464, lr = 0.010000 | |
| iter = 1966, accuracy (cur) = 0.780000 (all), 0.840000 (pos), 0.720000 (neg) | |
| iter = 1966, accuracy (avg) = 0.852404 (all), 0.857758 (pos), 0.846970 (neg) | |
| data reader: epoch = 0, batch = 1967 / 4040 | |
| iter = 1967, cls_loss (cur) = 0.327130, cls_loss (avg) = 0.324491, lr = 0.010000 | |
| iter = 1967, accuracy (cur) = 0.860000 (all), 0.904762 (pos), 0.827586 (neg) | |
| iter = 1967, accuracy (avg) = 0.852480 (all), 0.858228 (pos), 0.846776 (neg) | |
| data reader: epoch = 0, batch = 1968 / 4040 | |
| iter = 1968, cls_loss (cur) = 0.262524, cls_loss (avg) = 0.323871, lr = 0.010000 | |
| iter = 1968, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 1968, accuracy (avg) = 0.852755 (all), 0.857828 (pos), 0.847594 (neg) | |
| data reader: epoch = 0, batch = 1969 / 4040 | |
| iter = 1969, cls_loss (cur) = 0.412000, cls_loss (avg) = 0.324753, lr = 0.010000 | |
| iter = 1969, accuracy (cur) = 0.740000 (all), 0.730769 (pos), 0.750000 (neg) | |
| iter = 1969, accuracy (avg) = 0.851628 (all), 0.856557 (pos), 0.846618 (neg) | |
| data reader: epoch = 0, batch = 1970 / 4040 | |
| iter = 1970, cls_loss (cur) = 0.344075, cls_loss (avg) = 0.324946, lr = 0.010000 | |
| iter = 1970, accuracy (cur) = 0.820000 (all), 0.740741 (pos), 0.913043 (neg) | |
| iter = 1970, accuracy (avg) = 0.851312 (all), 0.855399 (pos), 0.847282 (neg) | |
| data reader: epoch = 0, batch = 1971 / 4040 | |
| iter = 1971, cls_loss (cur) = 0.359273, cls_loss (avg) = 0.325289, lr = 0.010000 | |
| iter = 1971, accuracy (cur) = 0.860000 (all), 0.913043 (pos), 0.814815 (neg) | |
| iter = 1971, accuracy (avg) = 0.851399 (all), 0.855975 (pos), 0.846958 (neg) | |
| data reader: epoch = 0, batch = 1972 / 4040 | |
| iter = 1972, cls_loss (cur) = 0.309116, cls_loss (avg) = 0.325127, lr = 0.010000 | |
| iter = 1972, accuracy (cur) = 0.840000 (all), 0.900000 (pos), 0.750000 (neg) | |
| iter = 1972, accuracy (avg) = 0.851285 (all), 0.856416 (pos), 0.845988 (neg) | |
| data reader: epoch = 0, batch = 1973 / 4040 | |
| iter = 1973, cls_loss (cur) = 0.293461, cls_loss (avg) = 0.324811, lr = 0.010000 | |
| iter = 1973, accuracy (cur) = 0.860000 (all), 0.884615 (pos), 0.833333 (neg) | |
| iter = 1973, accuracy (avg) = 0.851372 (all), 0.856698 (pos), 0.845861 (neg) | |
| data reader: epoch = 0, batch = 1974 / 4040 | |
| iter = 1974, cls_loss (cur) = 0.378831, cls_loss (avg) = 0.325351, lr = 0.010000 | |
| iter = 1974, accuracy (cur) = 0.880000 (all), 0.750000 (pos), 0.966667 (neg) | |
| iter = 1974, accuracy (avg) = 0.851658 (all), 0.855631 (pos), 0.847070 (neg) | |
| data reader: epoch = 0, batch = 1975 / 4040 | |
| iter = 1975, cls_loss (cur) = 0.276647, cls_loss (avg) = 0.324864, lr = 0.010000 | |
| iter = 1975, accuracy (cur) = 0.880000 (all), 0.916667 (pos), 0.846154 (neg) | |
| iter = 1975, accuracy (avg) = 0.851941 (all), 0.856241 (pos), 0.847060 (neg) | |
| data reader: epoch = 0, batch = 1976 / 4040 | |
| iter = 1976, cls_loss (cur) = 0.243259, cls_loss (avg) = 0.324048, lr = 0.010000 | |
| iter = 1976, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 1976, accuracy (avg) = 0.852422 (all), 0.856140 (pos), 0.848173 (neg) | |
| data reader: epoch = 0, batch = 1977 / 4040 | |
| iter = 1977, cls_loss (cur) = 0.335181, cls_loss (avg) = 0.324159, lr = 0.010000 | |
| iter = 1977, accuracy (cur) = 0.820000 (all), 0.826087 (pos), 0.814815 (neg) | |
| iter = 1977, accuracy (avg) = 0.852098 (all), 0.855840 (pos), 0.847840 (neg) | |
| data reader: epoch = 0, batch = 1978 / 4040 | |
| iter = 1978, cls_loss (cur) = 0.188665, cls_loss (avg) = 0.322804, lr = 0.010000 | |
| iter = 1978, accuracy (cur) = 0.920000 (all), 0.913043 (pos), 0.925926 (neg) | |
| iter = 1978, accuracy (avg) = 0.852777 (all), 0.856412 (pos), 0.848620 (neg) | |
| data reader: epoch = 0, batch = 1979 / 4040 | |
| iter = 1979, cls_loss (cur) = 0.290257, cls_loss (avg) = 0.322479, lr = 0.010000 | |
| iter = 1979, accuracy (cur) = 0.840000 (all), 0.769231 (pos), 0.916667 (neg) | |
| iter = 1979, accuracy (avg) = 0.852649 (all), 0.855540 (pos), 0.849301 (neg) | |
| data reader: epoch = 0, batch = 1980 / 4040 | |
| iter = 1980, cls_loss (cur) = 0.324812, cls_loss (avg) = 0.322502, lr = 0.010000 | |
| iter = 1980, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 1980, accuracy (avg) = 0.853123 (all), 0.856151 (pos), 0.849654 (neg) | |
| data reader: epoch = 0, batch = 1981 / 4040 | |
| iter = 1981, cls_loss (cur) = 0.204011, cls_loss (avg) = 0.321317, lr = 0.010000 | |
| iter = 1981, accuracy (cur) = 0.920000 (all), 0.920000 (pos), 0.920000 (neg) | |
| iter = 1981, accuracy (avg) = 0.853791 (all), 0.856790 (pos), 0.850357 (neg) | |
| data reader: epoch = 0, batch = 1982 / 4040 | |
| iter = 1982, cls_loss (cur) = 0.273058, cls_loss (avg) = 0.320835, lr = 0.010000 | |
| iter = 1982, accuracy (cur) = 0.860000 (all), 0.806452 (pos), 0.947368 (neg) | |
| iter = 1982, accuracy (avg) = 0.853853 (all), 0.856286 (pos), 0.851328 (neg) | |
| data reader: epoch = 0, batch = 1983 / 4040 | |
| iter = 1983, cls_loss (cur) = 0.350125, cls_loss (avg) = 0.321127, lr = 0.010000 | |
| iter = 1983, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.863636 (neg) | |
| iter = 1983, accuracy (avg) = 0.853915 (all), 0.856295 (pos), 0.851451 (neg) | |
| data reader: epoch = 0, batch = 1984 / 4040 | |
| iter = 1984, cls_loss (cur) = 0.238223, cls_loss (avg) = 0.320298, lr = 0.010000 | |
| iter = 1984, accuracy (cur) = 0.920000 (all), 0.965517 (pos), 0.857143 (neg) | |
| iter = 1984, accuracy (avg) = 0.854576 (all), 0.857387 (pos), 0.851508 (neg) | |
| data reader: epoch = 0, batch = 1985 / 4040 | |
| iter = 1985, cls_loss (cur) = 0.294555, cls_loss (avg) = 0.320041, lr = 0.010000 | |
| iter = 1985, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.857143 (neg) | |
| iter = 1985, accuracy (avg) = 0.854830 (all), 0.857904 (pos), 0.851564 (neg) | |
| data reader: epoch = 0, batch = 1986 / 4040 | |
| iter = 1986, cls_loss (cur) = 0.440249, cls_loss (avg) = 0.321243, lr = 0.010000 | |
| iter = 1986, accuracy (cur) = 0.760000 (all), 0.846154 (pos), 0.666667 (neg) | |
| iter = 1986, accuracy (avg) = 0.853882 (all), 0.857787 (pos), 0.849715 (neg) | |
| data reader: epoch = 0, batch = 1987 / 4040 | |
| iter = 1987, cls_loss (cur) = 0.265695, cls_loss (avg) = 0.320688, lr = 0.010000 | |
| iter = 1987, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 1987, accuracy (avg) = 0.853943 (all), 0.857829 (pos), 0.849789 (neg) | |
| data reader: epoch = 0, batch = 1988 / 4040 | |
| iter = 1988, cls_loss (cur) = 0.302597, cls_loss (avg) = 0.320507, lr = 0.010000 | |
| iter = 1988, accuracy (cur) = 0.880000 (all), 0.916667 (pos), 0.846154 (neg) | |
| iter = 1988, accuracy (avg) = 0.854203 (all), 0.858418 (pos), 0.849753 (neg) | |
| data reader: epoch = 0, batch = 1989 / 4040 | |
| iter = 1989, cls_loss (cur) = 0.319604, cls_loss (avg) = 0.320498, lr = 0.010000 | |
| iter = 1989, accuracy (cur) = 0.840000 (all), 1.000000 (pos), 0.750000 (neg) | |
| iter = 1989, accuracy (avg) = 0.854061 (all), 0.859834 (pos), 0.848755 (neg) | |
| data reader: epoch = 0, batch = 1990 / 4040 | |
| iter = 1990, cls_loss (cur) = 0.333630, cls_loss (avg) = 0.320629, lr = 0.010000 | |
| iter = 1990, accuracy (cur) = 0.860000 (all), 0.896552 (pos), 0.809524 (neg) | |
| iter = 1990, accuracy (avg) = 0.854121 (all), 0.860201 (pos), 0.848363 (neg) | |
| data reader: epoch = 0, batch = 1991 / 4040 | |
| iter = 1991, cls_loss (cur) = 0.297386, cls_loss (avg) = 0.320397, lr = 0.010000 | |
| iter = 1991, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 1991, accuracy (avg) = 0.853980 (all), 0.860349 (pos), 0.847956 (neg) | |
| data reader: epoch = 0, batch = 1992 / 4040 | |
| iter = 1992, cls_loss (cur) = 0.500581, cls_loss (avg) = 0.322198, lr = 0.010000 | |
| iter = 1992, accuracy (cur) = 0.760000 (all), 0.708333 (pos), 0.807692 (neg) | |
| iter = 1992, accuracy (avg) = 0.853040 (all), 0.858829 (pos), 0.847554 (neg) | |
| data reader: epoch = 0, batch = 1993 / 4040 | |
| iter = 1993, cls_loss (cur) = 0.394990, cls_loss (avg) = 0.322926, lr = 0.010000 | |
| iter = 1993, accuracy (cur) = 0.800000 (all), 0.760000 (pos), 0.840000 (neg) | |
| iter = 1993, accuracy (avg) = 0.852509 (all), 0.857840 (pos), 0.847478 (neg) | |
| data reader: epoch = 0, batch = 1994 / 4040 | |
| iter = 1994, cls_loss (cur) = 0.377794, cls_loss (avg) = 0.323475, lr = 0.010000 | |
| iter = 1994, accuracy (cur) = 0.800000 (all), 0.772727 (pos), 0.821429 (neg) | |
| iter = 1994, accuracy (avg) = 0.851984 (all), 0.856989 (pos), 0.847218 (neg) | |
| data reader: epoch = 0, batch = 1995 / 4040 | |
| iter = 1995, cls_loss (cur) = 0.296417, cls_loss (avg) = 0.323204, lr = 0.010000 | |
| iter = 1995, accuracy (cur) = 0.880000 (all), 0.862069 (pos), 0.904762 (neg) | |
| iter = 1995, accuracy (avg) = 0.852264 (all), 0.857040 (pos), 0.847793 (neg) | |
| data reader: epoch = 0, batch = 1996 / 4040 | |
| iter = 1996, cls_loss (cur) = 0.366743, cls_loss (avg) = 0.323640, lr = 0.010000 | |
| iter = 1996, accuracy (cur) = 0.820000 (all), 0.680000 (pos), 0.960000 (neg) | |
| iter = 1996, accuracy (avg) = 0.851942 (all), 0.855270 (pos), 0.848915 (neg) | |
| data reader: epoch = 0, batch = 1997 / 4040 | |
| iter = 1997, cls_loss (cur) = 0.227361, cls_loss (avg) = 0.322677, lr = 0.010000 | |
| iter = 1997, accuracy (cur) = 0.920000 (all), 0.916667 (pos), 0.923077 (neg) | |
| iter = 1997, accuracy (avg) = 0.852622 (all), 0.855884 (pos), 0.849657 (neg) | |
| data reader: epoch = 0, batch = 1998 / 4040 | |
| iter = 1998, cls_loss (cur) = 0.278539, cls_loss (avg) = 0.322236, lr = 0.010000 | |
| iter = 1998, accuracy (cur) = 0.860000 (all), 0.863636 (pos), 0.857143 (neg) | |
| iter = 1998, accuracy (avg) = 0.852696 (all), 0.855961 (pos), 0.849732 (neg) | |
| data reader: epoch = 0, batch = 1999 / 4040 | |
| iter = 1999, cls_loss (cur) = 0.282609, cls_loss (avg) = 0.321839, lr = 0.010000 | |
| iter = 1999, accuracy (cur) = 0.920000 (all), 0.920000 (pos), 0.920000 (neg) | |
| iter = 1999, accuracy (avg) = 0.853369 (all), 0.856601 (pos), 0.850434 (neg) | |
| data reader: epoch = 0, batch = 2000 / 4040 | |
| iter = 2000, cls_loss (cur) = 0.362248, cls_loss (avg) = 0.322243, lr = 0.010000 | |
| iter = 2000, accuracy (cur) = 0.880000 (all), 0.892857 (pos), 0.863636 (neg) | |
| iter = 2000, accuracy (avg) = 0.853635 (all), 0.856964 (pos), 0.850566 (neg) | |
| data reader: epoch = 0, batch = 2001 / 4040 | |
| iter = 2001, cls_loss (cur) = 0.405868, cls_loss (avg) = 0.323080, lr = 0.010000 | |
| iter = 2001, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 2001, accuracy (avg) = 0.853099 (all), 0.856394 (pos), 0.850061 (neg) | |
| data reader: epoch = 0, batch = 2002 / 4040 | |
| iter = 2002, cls_loss (cur) = 0.436995, cls_loss (avg) = 0.324219, lr = 0.010000 | |
| iter = 2002, accuracy (cur) = 0.800000 (all), 0.807692 (pos), 0.791667 (neg) | |
| iter = 2002, accuracy (avg) = 0.852568 (all), 0.855907 (pos), 0.849477 (neg) | |
| data reader: epoch = 0, batch = 2003 / 4040 | |
| iter = 2003, cls_loss (cur) = 0.309666, cls_loss (avg) = 0.324073, lr = 0.010000 | |
| iter = 2003, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 2003, accuracy (avg) = 0.853042 (all), 0.856548 (pos), 0.849782 (neg) | |
| data reader: epoch = 0, batch = 2004 / 4040 | |
| iter = 2004, cls_loss (cur) = 0.294611, cls_loss (avg) = 0.323779, lr = 0.010000 | |
| iter = 2004, accuracy (cur) = 0.860000 (all), 0.956522 (pos), 0.777778 (neg) | |
| iter = 2004, accuracy (avg) = 0.853112 (all), 0.857548 (pos), 0.849062 (neg) | |
| data reader: epoch = 0, batch = 2005 / 4040 | |
| iter = 2005, cls_loss (cur) = 0.370384, cls_loss (avg) = 0.324245, lr = 0.010000 | |
| iter = 2005, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 2005, accuracy (avg) = 0.852981 (all), 0.856889 (pos), 0.849417 (neg) | |
| data reader: epoch = 0, batch = 2006 / 4040 | |
| iter = 2006, cls_loss (cur) = 0.193707, cls_loss (avg) = 0.322939, lr = 0.010000 | |
| iter = 2006, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.916667 (neg) | |
| iter = 2006, accuracy (avg) = 0.854051 (all), 0.858320 (pos), 0.850090 (neg) | |
| data reader: epoch = 0, batch = 2007 / 4040 | |
| iter = 2007, cls_loss (cur) = 0.383270, cls_loss (avg) = 0.323543, lr = 0.010000 | |
| iter = 2007, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 2007, accuracy (avg) = 0.853711 (all), 0.857951 (pos), 0.849771 (neg) | |
| data reader: epoch = 0, batch = 2008 / 4040 | |
| iter = 2008, cls_loss (cur) = 0.201879, cls_loss (avg) = 0.322326, lr = 0.010000 | |
| iter = 2008, accuracy (cur) = 0.980000 (all), 0.972222 (pos), 1.000000 (neg) | |
| iter = 2008, accuracy (avg) = 0.854973 (all), 0.859094 (pos), 0.851273 (neg) | |
| data reader: epoch = 0, batch = 2009 / 4040 | |
| iter = 2009, cls_loss (cur) = 0.277093, cls_loss (avg) = 0.321874, lr = 0.010000 | |
| iter = 2009, accuracy (cur) = 0.880000 (all), 0.956522 (pos), 0.814815 (neg) | |
| iter = 2009, accuracy (avg) = 0.855224 (all), 0.860068 (pos), 0.850909 (neg) | |
| data reader: epoch = 0, batch = 2010 / 4040 | |
| iter = 2010, cls_loss (cur) = 0.370649, cls_loss (avg) = 0.322361, lr = 0.010000 | |
| iter = 2010, accuracy (cur) = 0.880000 (all), 0.952381 (pos), 0.827586 (neg) | |
| iter = 2010, accuracy (avg) = 0.855472 (all), 0.860992 (pos), 0.850675 (neg) | |
| data reader: epoch = 0, batch = 2011 / 4040 | |
| iter = 2011, cls_loss (cur) = 0.352886, cls_loss (avg) = 0.322667, lr = 0.010000 | |
| iter = 2011, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.862069 (neg) | |
| iter = 2011, accuracy (avg) = 0.855517 (all), 0.860953 (pos), 0.850789 (neg) | |
| data reader: epoch = 0, batch = 2012 / 4040 | |
| iter = 2012, cls_loss (cur) = 0.273491, cls_loss (avg) = 0.322175, lr = 0.010000 | |
| iter = 2012, accuracy (cur) = 0.840000 (all), 0.863636 (pos), 0.821429 (neg) | |
| iter = 2012, accuracy (avg) = 0.855362 (all), 0.860980 (pos), 0.850496 (neg) | |
| data reader: epoch = 0, batch = 2013 / 4040 | |
| iter = 2013, cls_loss (cur) = 0.321299, cls_loss (avg) = 0.322166, lr = 0.010000 | |
| iter = 2013, accuracy (cur) = 0.820000 (all), 0.846154 (pos), 0.791667 (neg) | |
| iter = 2013, accuracy (avg) = 0.855008 (all), 0.860832 (pos), 0.849907 (neg) | |
| data reader: epoch = 0, batch = 2014 / 4040 | |
| iter = 2014, cls_loss (cur) = 0.249656, cls_loss (avg) = 0.321441, lr = 0.010000 | |
| iter = 2014, accuracy (cur) = 0.860000 (all), 0.909091 (pos), 0.821429 (neg) | |
| iter = 2014, accuracy (avg) = 0.855058 (all), 0.861314 (pos), 0.849623 (neg) | |
| data reader: epoch = 0, batch = 2015 / 4040 | |
| iter = 2015, cls_loss (cur) = 0.322102, cls_loss (avg) = 0.321448, lr = 0.010000 | |
| iter = 2015, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 2015, accuracy (avg) = 0.855107 (all), 0.861220 (pos), 0.849822 (neg) | |
| data reader: epoch = 0, batch = 2016 / 4040 | |
| iter = 2016, cls_loss (cur) = 0.260175, cls_loss (avg) = 0.320835, lr = 0.010000 | |
| iter = 2016, accuracy (cur) = 0.920000 (all), 0.947368 (pos), 0.903226 (neg) | |
| iter = 2016, accuracy (avg) = 0.855756 (all), 0.862081 (pos), 0.850356 (neg) | |
| data reader: epoch = 0, batch = 2017 / 4040 | |
| iter = 2017, cls_loss (cur) = 0.297379, cls_loss (avg) = 0.320600, lr = 0.010000 | |
| iter = 2017, accuracy (cur) = 0.860000 (all), 0.894737 (pos), 0.838710 (neg) | |
| iter = 2017, accuracy (avg) = 0.855799 (all), 0.862408 (pos), 0.850240 (neg) | |
| data reader: epoch = 0, batch = 2018 / 4040 | |
| iter = 2018, cls_loss (cur) = 0.307946, cls_loss (avg) = 0.320474, lr = 0.010000 | |
| iter = 2018, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 2018, accuracy (avg) = 0.856241 (all), 0.862874 (pos), 0.850666 (neg) | |
| data reader: epoch = 0, batch = 2019 / 4040 | |
| iter = 2019, cls_loss (cur) = 0.287479, cls_loss (avg) = 0.320144, lr = 0.010000 | |
| iter = 2019, accuracy (cur) = 0.840000 (all), 0.761905 (pos), 0.896552 (neg) | |
| iter = 2019, accuracy (avg) = 0.856078 (all), 0.861865 (pos), 0.851125 (neg) | |
| data reader: epoch = 0, batch = 2020 / 4040 | |
| iter = 2020, cls_loss (cur) = 0.320158, cls_loss (avg) = 0.320144, lr = 0.010000 | |
| iter = 2020, accuracy (cur) = 0.860000 (all), 0.916667 (pos), 0.807692 (neg) | |
| iter = 2020, accuracy (avg) = 0.856118 (all), 0.862413 (pos), 0.850690 (neg) | |
| data reader: epoch = 0, batch = 2021 / 4040 | |
| iter = 2021, cls_loss (cur) = 0.273307, cls_loss (avg) = 0.319676, lr = 0.010000 | |
| iter = 2021, accuracy (cur) = 0.900000 (all), 0.904762 (pos), 0.896552 (neg) | |
| iter = 2021, accuracy (avg) = 0.856556 (all), 0.862836 (pos), 0.851149 (neg) | |
| data reader: epoch = 0, batch = 2022 / 4040 | |
| iter = 2022, cls_loss (cur) = 0.245135, cls_loss (avg) = 0.318930, lr = 0.010000 | |
| iter = 2022, accuracy (cur) = 0.900000 (all), 0.791667 (pos), 1.000000 (neg) | |
| iter = 2022, accuracy (avg) = 0.856991 (all), 0.862125 (pos), 0.852637 (neg) | |
| data reader: epoch = 0, batch = 2023 / 4040 | |
| iter = 2023, cls_loss (cur) = 0.276663, cls_loss (avg) = 0.318508, lr = 0.010000 | |
| iter = 2023, accuracy (cur) = 0.880000 (all), 0.807692 (pos), 0.958333 (neg) | |
| iter = 2023, accuracy (avg) = 0.857221 (all), 0.861580 (pos), 0.853694 (neg) | |
| data reader: epoch = 0, batch = 2024 / 4040 | |
| iter = 2024, cls_loss (cur) = 0.251945, cls_loss (avg) = 0.317842, lr = 0.010000 | |
| iter = 2024, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 2024, accuracy (avg) = 0.857049 (all), 0.860895 (pos), 0.854205 (neg) | |
| data reader: epoch = 0, batch = 2025 / 4040 | |
| iter = 2025, cls_loss (cur) = 0.321780, cls_loss (avg) = 0.317881, lr = 0.010000 | |
| iter = 2025, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 2025, accuracy (avg) = 0.857078 (all), 0.860748 (pos), 0.854413 (neg) | |
| data reader: epoch = 0, batch = 2026 / 4040 | |
| iter = 2026, cls_loss (cur) = 0.290611, cls_loss (avg) = 0.317609, lr = 0.010000 | |
| iter = 2026, accuracy (cur) = 0.880000 (all), 0.809524 (pos), 0.931034 (neg) | |
| iter = 2026, accuracy (avg) = 0.857307 (all), 0.860236 (pos), 0.855179 (neg) | |
| data reader: epoch = 0, batch = 2027 / 4040 | |
| iter = 2027, cls_loss (cur) = 0.271428, cls_loss (avg) = 0.317147, lr = 0.010000 | |
| iter = 2027, accuracy (cur) = 0.960000 (all), 0.960000 (pos), 0.960000 (neg) | |
| iter = 2027, accuracy (avg) = 0.858334 (all), 0.861233 (pos), 0.856227 (neg) | |
| data reader: epoch = 0, batch = 2028 / 4040 | |
| iter = 2028, cls_loss (cur) = 0.368470, cls_loss (avg) = 0.317660, lr = 0.010000 | |
| iter = 2028, accuracy (cur) = 0.800000 (all), 0.920000 (pos), 0.680000 (neg) | |
| iter = 2028, accuracy (avg) = 0.857751 (all), 0.861821 (pos), 0.854465 (neg) | |
| data reader: epoch = 0, batch = 2029 / 4040 | |
| iter = 2029, cls_loss (cur) = 0.280911, cls_loss (avg) = 0.317293, lr = 0.010000 | |
| iter = 2029, accuracy (cur) = 0.900000 (all), 0.904762 (pos), 0.896552 (neg) | |
| iter = 2029, accuracy (avg) = 0.858173 (all), 0.862251 (pos), 0.854886 (neg) | |
| data reader: epoch = 0, batch = 2030 / 4040 | |
| iter = 2030, cls_loss (cur) = 0.342872, cls_loss (avg) = 0.317548, lr = 0.010000 | |
| iter = 2030, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 2030, accuracy (avg) = 0.858192 (all), 0.862090 (pos), 0.855087 (neg) | |
| data reader: epoch = 0, batch = 2031 / 4040 | |
| iter = 2031, cls_loss (cur) = 0.244735, cls_loss (avg) = 0.316820, lr = 0.010000 | |
| iter = 2031, accuracy (cur) = 0.920000 (all), 0.909091 (pos), 0.928571 (neg) | |
| iter = 2031, accuracy (avg) = 0.858810 (all), 0.862560 (pos), 0.855822 (neg) | |
| data reader: epoch = 0, batch = 2032 / 4040 | |
| iter = 2032, cls_loss (cur) = 0.301899, cls_loss (avg) = 0.316671, lr = 0.010000 | |
| iter = 2032, accuracy (cur) = 0.840000 (all), 0.880000 (pos), 0.800000 (neg) | |
| iter = 2032, accuracy (avg) = 0.858622 (all), 0.862734 (pos), 0.855264 (neg) | |
| data reader: epoch = 0, batch = 2033 / 4040 | |
| iter = 2033, cls_loss (cur) = 0.265132, cls_loss (avg) = 0.316156, lr = 0.010000 | |
| iter = 2033, accuracy (cur) = 0.920000 (all), 0.826087 (pos), 1.000000 (neg) | |
| iter = 2033, accuracy (avg) = 0.859236 (all), 0.862368 (pos), 0.856711 (neg) | |
| data reader: epoch = 0, batch = 2034 / 4040 | |
| iter = 2034, cls_loss (cur) = 0.257116, cls_loss (avg) = 0.315565, lr = 0.010000 | |
| iter = 2034, accuracy (cur) = 0.940000 (all), 0.928571 (pos), 0.954545 (neg) | |
| iter = 2034, accuracy (avg) = 0.860043 (all), 0.863030 (pos), 0.857690 (neg) | |
| data reader: epoch = 0, batch = 2035 / 4040 | |
| iter = 2035, cls_loss (cur) = 0.308709, cls_loss (avg) = 0.315497, lr = 0.010000 | |
| iter = 2035, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 2035, accuracy (avg) = 0.859843 (all), 0.862399 (pos), 0.857779 (neg) | |
| data reader: epoch = 0, batch = 2036 / 4040 | |
| iter = 2036, cls_loss (cur) = 0.245389, cls_loss (avg) = 0.314796, lr = 0.010000 | |
| iter = 2036, accuracy (cur) = 0.940000 (all), 0.916667 (pos), 0.961538 (neg) | |
| iter = 2036, accuracy (avg) = 0.860644 (all), 0.862942 (pos), 0.858817 (neg) | |
| data reader: epoch = 0, batch = 2037 / 4040 | |
| iter = 2037, cls_loss (cur) = 0.309828, cls_loss (avg) = 0.314746, lr = 0.010000 | |
| iter = 2037, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 2037, accuracy (avg) = 0.860438 (all), 0.862646 (pos), 0.858690 (neg) | |
| data reader: epoch = 0, batch = 2038 / 4040 | |
| iter = 2038, cls_loss (cur) = 0.264776, cls_loss (avg) = 0.314246, lr = 0.010000 | |
| iter = 2038, accuracy (cur) = 0.880000 (all), 0.884615 (pos), 0.875000 (neg) | |
| iter = 2038, accuracy (avg) = 0.860633 (all), 0.862866 (pos), 0.858853 (neg) | |
| data reader: epoch = 0, batch = 2039 / 4040 | |
| iter = 2039, cls_loss (cur) = 0.397029, cls_loss (avg) = 0.315074, lr = 0.010000 | |
| iter = 2039, accuracy (cur) = 0.800000 (all), 0.809524 (pos), 0.793103 (neg) | |
| iter = 2039, accuracy (avg) = 0.860027 (all), 0.862332 (pos), 0.858196 (neg) | |
| data reader: epoch = 0, batch = 2040 / 4040 | |
| iter = 2040, cls_loss (cur) = 0.243218, cls_loss (avg) = 0.314356, lr = 0.010000 | |
| iter = 2040, accuracy (cur) = 0.920000 (all), 0.964286 (pos), 0.863636 (neg) | |
| iter = 2040, accuracy (avg) = 0.860627 (all), 0.863352 (pos), 0.858250 (neg) | |
| data reader: epoch = 0, batch = 2041 / 4040 | |
| iter = 2041, cls_loss (cur) = 0.309760, cls_loss (avg) = 0.314310, lr = 0.010000 | |
| iter = 2041, accuracy (cur) = 0.920000 (all), 0.869565 (pos), 0.962963 (neg) | |
| iter = 2041, accuracy (avg) = 0.861221 (all), 0.863414 (pos), 0.859297 (neg) | |
| data reader: epoch = 0, batch = 2042 / 4040 | |
| iter = 2042, cls_loss (cur) = 0.237734, cls_loss (avg) = 0.313544, lr = 0.010000 | |
| iter = 2042, accuracy (cur) = 0.900000 (all), 0.909091 (pos), 0.892857 (neg) | |
| iter = 2042, accuracy (avg) = 0.861608 (all), 0.863871 (pos), 0.859633 (neg) | |
| data reader: epoch = 0, batch = 2043 / 4040 | |
| iter = 2043, cls_loss (cur) = 0.225537, cls_loss (avg) = 0.312664, lr = 0.010000 | |
| iter = 2043, accuracy (cur) = 0.940000 (all), 0.935484 (pos), 0.947368 (neg) | |
| iter = 2043, accuracy (avg) = 0.862392 (all), 0.864587 (pos), 0.860510 (neg) | |
| data reader: epoch = 0, batch = 2044 / 4040 | |
| iter = 2044, cls_loss (cur) = 0.243436, cls_loss (avg) = 0.311971, lr = 0.010000 | |
| iter = 2044, accuracy (cur) = 0.880000 (all), 0.909091 (pos), 0.823529 (neg) | |
| iter = 2044, accuracy (avg) = 0.862568 (all), 0.865032 (pos), 0.860141 (neg) | |
| data reader: epoch = 0, batch = 2045 / 4040 | |
| iter = 2045, cls_loss (cur) = 0.370541, cls_loss (avg) = 0.312557, lr = 0.010000 | |
| iter = 2045, accuracy (cur) = 0.800000 (all), 0.793103 (pos), 0.809524 (neg) | |
| iter = 2045, accuracy (avg) = 0.861943 (all), 0.864312 (pos), 0.859634 (neg) | |
| data reader: epoch = 0, batch = 2046 / 4040 | |
| iter = 2046, cls_loss (cur) = 0.294327, cls_loss (avg) = 0.312375, lr = 0.010000 | |
| iter = 2046, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 2046, accuracy (avg) = 0.862123 (all), 0.863930 (pos), 0.860297 (neg) | |
| data reader: epoch = 0, batch = 2047 / 4040 | |
| iter = 2047, cls_loss (cur) = 0.340413, cls_loss (avg) = 0.312655, lr = 0.010000 | |
| iter = 2047, accuracy (cur) = 0.820000 (all), 0.848485 (pos), 0.764706 (neg) | |
| iter = 2047, accuracy (avg) = 0.861702 (all), 0.863776 (pos), 0.859341 (neg) | |
| data reader: epoch = 0, batch = 2048 / 4040 | |
| iter = 2048, cls_loss (cur) = 0.225200, cls_loss (avg) = 0.311781, lr = 0.010000 | |
| iter = 2048, accuracy (cur) = 0.900000 (all), 0.956522 (pos), 0.851852 (neg) | |
| iter = 2048, accuracy (avg) = 0.862085 (all), 0.864703 (pos), 0.859266 (neg) | |
| data reader: epoch = 0, batch = 2049 / 4040 | |
| iter = 2049, cls_loss (cur) = 0.370737, cls_loss (avg) = 0.312370, lr = 0.010000 | |
| iter = 2049, accuracy (cur) = 0.820000 (all), 0.821429 (pos), 0.818182 (neg) | |
| iter = 2049, accuracy (avg) = 0.861664 (all), 0.864270 (pos), 0.858856 (neg) | |
| data reader: epoch = 0, batch = 2050 / 4040 | |
| iter = 2050, cls_loss (cur) = 0.227825, cls_loss (avg) = 0.311525, lr = 0.010000 | |
| iter = 2050, accuracy (cur) = 0.940000 (all), 0.968750 (pos), 0.888889 (neg) | |
| iter = 2050, accuracy (avg) = 0.862448 (all), 0.865315 (pos), 0.859156 (neg) | |
| data reader: epoch = 0, batch = 2051 / 4040 | |
| iter = 2051, cls_loss (cur) = 0.353947, cls_loss (avg) = 0.311949, lr = 0.010000 | |
| iter = 2051, accuracy (cur) = 0.840000 (all), 0.916667 (pos), 0.769231 (neg) | |
| iter = 2051, accuracy (avg) = 0.862223 (all), 0.865829 (pos), 0.858257 (neg) | |
| data reader: epoch = 0, batch = 2052 / 4040 | |
| iter = 2052, cls_loss (cur) = 0.354370, cls_loss (avg) = 0.312373, lr = 0.010000 | |
| iter = 2052, accuracy (cur) = 0.820000 (all), 0.785714 (pos), 0.863636 (neg) | |
| iter = 2052, accuracy (avg) = 0.861801 (all), 0.865028 (pos), 0.858310 (neg) | |
| data reader: epoch = 0, batch = 2053 / 4040 | |
| iter = 2053, cls_loss (cur) = 0.265898, cls_loss (avg) = 0.311908, lr = 0.010000 | |
| iter = 2053, accuracy (cur) = 0.920000 (all), 0.923077 (pos), 0.916667 (neg) | |
| iter = 2053, accuracy (avg) = 0.862383 (all), 0.865608 (pos), 0.858894 (neg) | |
| data reader: epoch = 0, batch = 2054 / 4040 | |
| iter = 2054, cls_loss (cur) = 0.373173, cls_loss (avg) = 0.312521, lr = 0.010000 | |
| iter = 2054, accuracy (cur) = 0.820000 (all), 0.952381 (pos), 0.724138 (neg) | |
| iter = 2054, accuracy (avg) = 0.861959 (all), 0.866476 (pos), 0.857546 (neg) | |
| data reader: epoch = 0, batch = 2055 / 4040 | |
| iter = 2055, cls_loss (cur) = 0.258569, cls_loss (avg) = 0.311982, lr = 0.010000 | |
| iter = 2055, accuracy (cur) = 0.940000 (all), 0.961538 (pos), 0.916667 (neg) | |
| iter = 2055, accuracy (avg) = 0.862739 (all), 0.867426 (pos), 0.858138 (neg) | |
| data reader: epoch = 0, batch = 2056 / 4040 | |
| iter = 2056, cls_loss (cur) = 0.479681, cls_loss (avg) = 0.313659, lr = 0.010000 | |
| iter = 2056, accuracy (cur) = 0.800000 (all), 0.684211 (pos), 0.870968 (neg) | |
| iter = 2056, accuracy (avg) = 0.862112 (all), 0.865594 (pos), 0.858266 (neg) | |
| data reader: epoch = 0, batch = 2057 / 4040 | |
| iter = 2057, cls_loss (cur) = 0.320898, cls_loss (avg) = 0.313731, lr = 0.010000 | |
| iter = 2057, accuracy (cur) = 0.800000 (all), 0.793103 (pos), 0.809524 (neg) | |
| iter = 2057, accuracy (avg) = 0.861491 (all), 0.864869 (pos), 0.857779 (neg) | |
| data reader: epoch = 0, batch = 2058 / 4040 | |
| iter = 2058, cls_loss (cur) = 0.257382, cls_loss (avg) = 0.313167, lr = 0.010000 | |
| iter = 2058, accuracy (cur) = 0.940000 (all), 0.925926 (pos), 0.956522 (neg) | |
| iter = 2058, accuracy (avg) = 0.862276 (all), 0.865480 (pos), 0.858766 (neg) | |
| data reader: epoch = 0, batch = 2059 / 4040 | |
| iter = 2059, cls_loss (cur) = 0.268467, cls_loss (avg) = 0.312720, lr = 0.010000 | |
| iter = 2059, accuracy (cur) = 0.920000 (all), 0.956522 (pos), 0.888889 (neg) | |
| iter = 2059, accuracy (avg) = 0.862853 (all), 0.866390 (pos), 0.859067 (neg) | |
| data reader: epoch = 0, batch = 2060 / 4040 | |
| iter = 2060, cls_loss (cur) = 0.311633, cls_loss (avg) = 0.312710, lr = 0.010000 | |
| iter = 2060, accuracy (cur) = 0.840000 (all), 0.826087 (pos), 0.851852 (neg) | |
| iter = 2060, accuracy (avg) = 0.862625 (all), 0.865987 (pos), 0.858995 (neg) | |
| data reader: epoch = 0, batch = 2061 / 4040 | |
| iter = 2061, cls_loss (cur) = 0.290919, cls_loss (avg) = 0.312492, lr = 0.010000 | |
| iter = 2061, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 2061, accuracy (avg) = 0.862598 (all), 0.865846 (pos), 0.859101 (neg) | |
| data reader: epoch = 0, batch = 2062 / 4040 | |
| iter = 2062, cls_loss (cur) = 0.409591, cls_loss (avg) = 0.313463, lr = 0.010000 | |
| iter = 2062, accuracy (cur) = 0.820000 (all), 0.840000 (pos), 0.800000 (neg) | |
| iter = 2062, accuracy (avg) = 0.862172 (all), 0.865588 (pos), 0.858510 (neg) | |
| data reader: epoch = 0, batch = 2063 / 4040 | |
| iter = 2063, cls_loss (cur) = 0.257829, cls_loss (avg) = 0.312906, lr = 0.010000 | |
| iter = 2063, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.942857 (neg) | |
| iter = 2063, accuracy (avg) = 0.863151 (all), 0.866932 (pos), 0.859353 (neg) | |
| data reader: epoch = 0, batch = 2064 / 4040 | |
| iter = 2064, cls_loss (cur) = 0.273287, cls_loss (avg) = 0.312510, lr = 0.010000 | |
| iter = 2064, accuracy (cur) = 0.880000 (all), 0.950000 (pos), 0.833333 (neg) | |
| iter = 2064, accuracy (avg) = 0.863319 (all), 0.867762 (pos), 0.859093 (neg) | |
| data reader: epoch = 0, batch = 2065 / 4040 | |
| iter = 2065, cls_loss (cur) = 0.214862, cls_loss (avg) = 0.311534, lr = 0.010000 | |
| iter = 2065, accuracy (cur) = 0.940000 (all), 0.900000 (pos), 0.966667 (neg) | |
| iter = 2065, accuracy (avg) = 0.864086 (all), 0.868085 (pos), 0.860169 (neg) | |
| data reader: epoch = 0, batch = 2066 / 4040 | |
| iter = 2066, cls_loss (cur) = 0.284958, cls_loss (avg) = 0.311268, lr = 0.010000 | |
| iter = 2066, accuracy (cur) = 0.900000 (all), 0.800000 (pos), 0.966667 (neg) | |
| iter = 2066, accuracy (avg) = 0.864445 (all), 0.867404 (pos), 0.861234 (neg) | |
| data reader: epoch = 0, batch = 2067 / 4040 | |
| iter = 2067, cls_loss (cur) = 0.456154, cls_loss (avg) = 0.312717, lr = 0.010000 | |
| iter = 2067, accuracy (cur) = 0.820000 (all), 0.782609 (pos), 0.851852 (neg) | |
| iter = 2067, accuracy (avg) = 0.864001 (all), 0.866556 (pos), 0.861140 (neg) | |
| data reader: epoch = 0, batch = 2068 / 4040 | |
| iter = 2068, cls_loss (cur) = 0.309916, cls_loss (avg) = 0.312689, lr = 0.010000 | |
| iter = 2068, accuracy (cur) = 0.860000 (all), 0.846154 (pos), 0.875000 (neg) | |
| iter = 2068, accuracy (avg) = 0.863961 (all), 0.866352 (pos), 0.861279 (neg) | |
| data reader: epoch = 0, batch = 2069 / 4040 | |
| iter = 2069, cls_loss (cur) = 0.248041, cls_loss (avg) = 0.312042, lr = 0.010000 | |
| iter = 2069, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.892857 (neg) | |
| iter = 2069, accuracy (avg) = 0.864721 (all), 0.867688 (pos), 0.861594 (neg) | |
| data reader: epoch = 0, batch = 2070 / 4040 | |
| iter = 2070, cls_loss (cur) = 0.305951, cls_loss (avg) = 0.311981, lr = 0.010000 | |
| iter = 2070, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 2070, accuracy (avg) = 0.864474 (all), 0.867762 (pos), 0.861055 (neg) | |
| data reader: epoch = 0, batch = 2071 / 4040 | |
| iter = 2071, cls_loss (cur) = 0.276958, cls_loss (avg) = 0.311631, lr = 0.010000 | |
| iter = 2071, accuracy (cur) = 0.880000 (all), 0.925926 (pos), 0.826087 (neg) | |
| iter = 2071, accuracy (avg) = 0.864629 (all), 0.868343 (pos), 0.860706 (neg) | |
| data reader: epoch = 0, batch = 2072 / 4040 | |
| iter = 2072, cls_loss (cur) = 0.253749, cls_loss (avg) = 0.311052, lr = 0.010000 | |
| iter = 2072, accuracy (cur) = 0.880000 (all), 0.851852 (pos), 0.913043 (neg) | |
| iter = 2072, accuracy (avg) = 0.864783 (all), 0.868178 (pos), 0.861229 (neg) | |
| data reader: epoch = 0, batch = 2073 / 4040 | |
| iter = 2073, cls_loss (cur) = 0.319218, cls_loss (avg) = 0.311134, lr = 0.010000 | |
| iter = 2073, accuracy (cur) = 0.920000 (all), 0.970588 (pos), 0.812500 (neg) | |
| iter = 2073, accuracy (avg) = 0.865335 (all), 0.869202 (pos), 0.860742 (neg) | |
| data reader: epoch = 0, batch = 2074 / 4040 | |
| iter = 2074, cls_loss (cur) = 0.262532, cls_loss (avg) = 0.310648, lr = 0.010000 | |
| iter = 2074, accuracy (cur) = 0.900000 (all), 0.896552 (pos), 0.904762 (neg) | |
| iter = 2074, accuracy (avg) = 0.865682 (all), 0.869476 (pos), 0.861182 (neg) | |
| data reader: epoch = 0, batch = 2075 / 4040 | |
| iter = 2075, cls_loss (cur) = 0.218014, cls_loss (avg) = 0.309722, lr = 0.010000 | |
| iter = 2075, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.840000 (neg) | |
| iter = 2075, accuracy (avg) = 0.866225 (all), 0.870781 (pos), 0.860970 (neg) | |
| data reader: epoch = 0, batch = 2076 / 4040 | |
| iter = 2076, cls_loss (cur) = 0.265889, cls_loss (avg) = 0.309283, lr = 0.010000 | |
| iter = 2076, accuracy (cur) = 0.940000 (all), 0.956522 (pos), 0.925926 (neg) | |
| iter = 2076, accuracy (avg) = 0.866963 (all), 0.871638 (pos), 0.861620 (neg) | |
| data reader: epoch = 0, batch = 2077 / 4040 | |
| iter = 2077, cls_loss (cur) = 0.238278, cls_loss (avg) = 0.308573, lr = 0.010000 | |
| iter = 2077, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.954545 (neg) | |
| iter = 2077, accuracy (avg) = 0.867293 (all), 0.871494 (pos), 0.862549 (neg) | |
| data reader: epoch = 0, batch = 2078 / 4040 | |
| iter = 2078, cls_loss (cur) = 0.272776, cls_loss (avg) = 0.308215, lr = 0.010000 | |
| iter = 2078, accuracy (cur) = 0.880000 (all), 0.962963 (pos), 0.782609 (neg) | |
| iter = 2078, accuracy (avg) = 0.867420 (all), 0.872408 (pos), 0.861750 (neg) | |
| data reader: epoch = 0, batch = 2079 / 4040 | |
| iter = 2079, cls_loss (cur) = 0.351406, cls_loss (avg) = 0.308647, lr = 0.010000 | |
| iter = 2079, accuracy (cur) = 0.840000 (all), 0.806452 (pos), 0.894737 (neg) | |
| iter = 2079, accuracy (avg) = 0.867146 (all), 0.871749 (pos), 0.862079 (neg) | |
| data reader: epoch = 0, batch = 2080 / 4040 | |
| iter = 2080, cls_loss (cur) = 0.409968, cls_loss (avg) = 0.309660, lr = 0.010000 | |
| iter = 2080, accuracy (cur) = 0.760000 (all), 0.781250 (pos), 0.722222 (neg) | |
| iter = 2080, accuracy (avg) = 0.866074 (all), 0.870844 (pos), 0.860681 (neg) | |
| data reader: epoch = 0, batch = 2081 / 4040 | |
| iter = 2081, cls_loss (cur) = 0.428026, cls_loss (avg) = 0.310844, lr = 0.010000 | |
| iter = 2081, accuracy (cur) = 0.760000 (all), 0.904762 (pos), 0.655172 (neg) | |
| iter = 2081, accuracy (avg) = 0.865014 (all), 0.871183 (pos), 0.858626 (neg) | |
| data reader: epoch = 0, batch = 2082 / 4040 | |
| iter = 2082, cls_loss (cur) = 0.306379, cls_loss (avg) = 0.310799, lr = 0.010000 | |
| iter = 2082, accuracy (cur) = 0.860000 (all), 0.875000 (pos), 0.846154 (neg) | |
| iter = 2082, accuracy (avg) = 0.864964 (all), 0.871221 (pos), 0.858501 (neg) | |
| data reader: epoch = 0, batch = 2083 / 4040 | |
| iter = 2083, cls_loss (cur) = 0.207917, cls_loss (avg) = 0.309771, lr = 0.010000 | |
| iter = 2083, accuracy (cur) = 0.920000 (all), 0.892857 (pos), 0.954545 (neg) | |
| iter = 2083, accuracy (avg) = 0.865514 (all), 0.871437 (pos), 0.859461 (neg) | |
| data reader: epoch = 0, batch = 2084 / 4040 | |
| iter = 2084, cls_loss (cur) = 0.295551, cls_loss (avg) = 0.309628, lr = 0.010000 | |
| iter = 2084, accuracy (cur) = 0.860000 (all), 0.807692 (pos), 0.916667 (neg) | |
| iter = 2084, accuracy (avg) = 0.865459 (all), 0.870800 (pos), 0.860034 (neg) | |
| data reader: epoch = 0, batch = 2085 / 4040 | |
| iter = 2085, cls_loss (cur) = 0.345029, cls_loss (avg) = 0.309982, lr = 0.010000 | |
| iter = 2085, accuracy (cur) = 0.860000 (all), 0.772727 (pos), 0.928571 (neg) | |
| iter = 2085, accuracy (avg) = 0.865404 (all), 0.869819 (pos), 0.860719 (neg) | |
| data reader: epoch = 0, batch = 2086 / 4040 | |
| iter = 2086, cls_loss (cur) = 0.508695, cls_loss (avg) = 0.311969, lr = 0.010000 | |
| iter = 2086, accuracy (cur) = 0.760000 (all), 0.807692 (pos), 0.708333 (neg) | |
| iter = 2086, accuracy (avg) = 0.864350 (all), 0.869198 (pos), 0.859195 (neg) | |
| data reader: epoch = 0, batch = 2087 / 4040 | |
| iter = 2087, cls_loss (cur) = 0.232353, cls_loss (avg) = 0.311173, lr = 0.010000 | |
| iter = 2087, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 2087, accuracy (avg) = 0.864707 (all), 0.869706 (pos), 0.859403 (neg) | |
| data reader: epoch = 0, batch = 2088 / 4040 | |
| iter = 2088, cls_loss (cur) = 0.283879, cls_loss (avg) = 0.310900, lr = 0.010000 | |
| iter = 2088, accuracy (cur) = 0.920000 (all), 0.900000 (pos), 0.950000 (neg) | |
| iter = 2088, accuracy (avg) = 0.865260 (all), 0.870009 (pos), 0.860309 (neg) | |
| data reader: epoch = 0, batch = 2089 / 4040 | |
| iter = 2089, cls_loss (cur) = 0.253704, cls_loss (avg) = 0.310328, lr = 0.010000 | |
| iter = 2089, accuracy (cur) = 0.900000 (all), 0.958333 (pos), 0.846154 (neg) | |
| iter = 2089, accuracy (avg) = 0.865607 (all), 0.870892 (pos), 0.860167 (neg) | |
| data reader: epoch = 0, batch = 2090 / 4040 | |
| iter = 2090, cls_loss (cur) = 0.249638, cls_loss (avg) = 0.309722, lr = 0.010000 | |
| iter = 2090, accuracy (cur) = 0.920000 (all), 0.954545 (pos), 0.892857 (neg) | |
| iter = 2090, accuracy (avg) = 0.866151 (all), 0.871729 (pos), 0.860494 (neg) | |
| data reader: epoch = 0, batch = 2091 / 4040 | |
| iter = 2091, cls_loss (cur) = 0.282405, cls_loss (avg) = 0.309448, lr = 0.010000 | |
| iter = 2091, accuracy (cur) = 0.900000 (all), 0.950000 (pos), 0.866667 (neg) | |
| iter = 2091, accuracy (avg) = 0.866489 (all), 0.872511 (pos), 0.860556 (neg) | |
| data reader: epoch = 0, batch = 2092 / 4040 | |
| iter = 2092, cls_loss (cur) = 0.281217, cls_loss (avg) = 0.309166, lr = 0.010000 | |
| iter = 2092, accuracy (cur) = 0.900000 (all), 0.884615 (pos), 0.916667 (neg) | |
| iter = 2092, accuracy (avg) = 0.866824 (all), 0.872632 (pos), 0.861117 (neg) | |
| data reader: epoch = 0, batch = 2093 / 4040 | |
| iter = 2093, cls_loss (cur) = 0.218530, cls_loss (avg) = 0.308260, lr = 0.010000 | |
| iter = 2093, accuracy (cur) = 0.900000 (all), 0.882353 (pos), 0.909091 (neg) | |
| iter = 2093, accuracy (avg) = 0.867156 (all), 0.872730 (pos), 0.861597 (neg) | |
| data reader: epoch = 0, batch = 2094 / 4040 | |
| iter = 2094, cls_loss (cur) = 0.335745, cls_loss (avg) = 0.308535, lr = 0.010000 | |
| iter = 2094, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 2094, accuracy (avg) = 0.867085 (all), 0.872521 (pos), 0.861677 (neg) | |
| data reader: epoch = 0, batch = 2095 / 4040 | |
| iter = 2095, cls_loss (cur) = 0.312170, cls_loss (avg) = 0.308571, lr = 0.010000 | |
| iter = 2095, accuracy (cur) = 0.900000 (all), 0.913043 (pos), 0.888889 (neg) | |
| iter = 2095, accuracy (avg) = 0.867414 (all), 0.872926 (pos), 0.861949 (neg) | |
| data reader: epoch = 0, batch = 2096 / 4040 | |
| iter = 2096, cls_loss (cur) = 0.274064, cls_loss (avg) = 0.308226, lr = 0.010000 | |
| iter = 2096, accuracy (cur) = 0.920000 (all), 0.933333 (pos), 0.914286 (neg) | |
| iter = 2096, accuracy (avg) = 0.867940 (all), 0.873530 (pos), 0.862472 (neg) | |
| data reader: epoch = 0, batch = 2097 / 4040 | |
| iter = 2097, cls_loss (cur) = 0.332793, cls_loss (avg) = 0.308471, lr = 0.010000 | |
| iter = 2097, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.909091 (neg) | |
| iter = 2097, accuracy (avg) = 0.867460 (all), 0.872295 (pos), 0.862938 (neg) | |
| data reader: epoch = 0, batch = 2098 / 4040 | |
| iter = 2098, cls_loss (cur) = 0.276552, cls_loss (avg) = 0.308152, lr = 0.010000 | |
| iter = 2098, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 2098, accuracy (avg) = 0.867586 (all), 0.872803 (pos), 0.862642 (neg) | |
| data reader: epoch = 0, batch = 2099 / 4040 | |
| iter = 2099, cls_loss (cur) = 0.321009, cls_loss (avg) = 0.308281, lr = 0.010000 | |
| iter = 2099, accuracy (cur) = 0.920000 (all), 0.900000 (pos), 0.950000 (neg) | |
| iter = 2099, accuracy (avg) = 0.868110 (all), 0.873075 (pos), 0.863516 (neg) | |
| data reader: epoch = 0, batch = 2100 / 4040 | |
| iter = 2100, cls_loss (cur) = 0.273779, cls_loss (avg) = 0.307936, lr = 0.010000 | |
| iter = 2100, accuracy (cur) = 0.900000 (all), 0.916667 (pos), 0.884615 (neg) | |
| iter = 2100, accuracy (avg) = 0.868429 (all), 0.873511 (pos), 0.863727 (neg) | |
| data reader: epoch = 0, batch = 2101 / 4040 | |
| iter = 2101, cls_loss (cur) = 0.226612, cls_loss (avg) = 0.307123, lr = 0.010000 | |
| iter = 2101, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 2101, accuracy (avg) = 0.868744 (all), 0.873525 (pos), 0.864320 (neg) | |
| data reader: epoch = 0, batch = 2102 / 4040 | |
| iter = 2102, cls_loss (cur) = 0.256021, cls_loss (avg) = 0.306612, lr = 0.010000 | |
| iter = 2102, accuracy (cur) = 0.920000 (all), 0.928571 (pos), 0.909091 (neg) | |
| iter = 2102, accuracy (avg) = 0.869257 (all), 0.874076 (pos), 0.864768 (neg) | |
| data reader: epoch = 0, batch = 2103 / 4040 | |
| iter = 2103, cls_loss (cur) = 0.407146, cls_loss (avg) = 0.307617, lr = 0.010000 | |
| iter = 2103, accuracy (cur) = 0.880000 (all), 0.857143 (pos), 0.896552 (neg) | |
| iter = 2103, accuracy (avg) = 0.869364 (all), 0.873907 (pos), 0.865086 (neg) | |
| data reader: epoch = 0, batch = 2104 / 4040 | |
| iter = 2104, cls_loss (cur) = 0.383184, cls_loss (avg) = 0.308373, lr = 0.010000 | |
| iter = 2104, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.850000 (neg) | |
| iter = 2104, accuracy (avg) = 0.869071 (all), 0.873501 (pos), 0.864935 (neg) | |
| data reader: epoch = 0, batch = 2105 / 4040 | |
| iter = 2105, cls_loss (cur) = 0.314336, cls_loss (avg) = 0.308432, lr = 0.010000 | |
| iter = 2105, accuracy (cur) = 0.840000 (all), 0.892857 (pos), 0.772727 (neg) | |
| iter = 2105, accuracy (avg) = 0.868780 (all), 0.873694 (pos), 0.864013 (neg) | |
| data reader: epoch = 0, batch = 2106 / 4040 | |
| iter = 2106, cls_loss (cur) = 0.271295, cls_loss (avg) = 0.308061, lr = 0.010000 | |
| iter = 2106, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 2106, accuracy (avg) = 0.868692 (all), 0.873886 (pos), 0.863555 (neg) | |
| data reader: epoch = 0, batch = 2107 / 4040 | |
| iter = 2107, cls_loss (cur) = 0.209904, cls_loss (avg) = 0.307079, lr = 0.010000 | |
| iter = 2107, accuracy (cur) = 0.920000 (all), 0.954545 (pos), 0.892857 (neg) | |
| iter = 2107, accuracy (avg) = 0.869205 (all), 0.874693 (pos), 0.863848 (neg) | |
| data reader: epoch = 0, batch = 2108 / 4040 | |
| iter = 2108, cls_loss (cur) = 0.381868, cls_loss (avg) = 0.307827, lr = 0.010000 | |
| iter = 2108, accuracy (cur) = 0.840000 (all), 0.966667 (pos), 0.650000 (neg) | |
| iter = 2108, accuracy (avg) = 0.868913 (all), 0.875612 (pos), 0.861709 (neg) | |
| data reader: epoch = 0, batch = 2109 / 4040 | |
| iter = 2109, cls_loss (cur) = 0.286851, cls_loss (avg) = 0.307617, lr = 0.010000 | |
| iter = 2109, accuracy (cur) = 0.880000 (all), 1.000000 (pos), 0.800000 (neg) | |
| iter = 2109, accuracy (avg) = 0.869024 (all), 0.876856 (pos), 0.861092 (neg) | |
| data reader: epoch = 0, batch = 2110 / 4040 | |
| iter = 2110, cls_loss (cur) = 0.300785, cls_loss (avg) = 0.307549, lr = 0.010000 | |
| iter = 2110, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 2110, accuracy (avg) = 0.869134 (all), 0.877318 (pos), 0.860815 (neg) | |
| data reader: epoch = 0, batch = 2111 / 4040 | |
| iter = 2111, cls_loss (cur) = 0.249993, cls_loss (avg) = 0.306974, lr = 0.010000 | |
| iter = 2111, accuracy (cur) = 0.920000 (all), 0.900000 (pos), 0.950000 (neg) | |
| iter = 2111, accuracy (avg) = 0.869643 (all), 0.877545 (pos), 0.861706 (neg) | |
| data reader: epoch = 0, batch = 2112 / 4040 | |
| iter = 2112, cls_loss (cur) = 0.219893, cls_loss (avg) = 0.306103, lr = 0.010000 | |
| iter = 2112, accuracy (cur) = 0.920000 (all), 0.961538 (pos), 0.875000 (neg) | |
| iter = 2112, accuracy (avg) = 0.870146 (all), 0.878385 (pos), 0.861839 (neg) | |
| data reader: epoch = 0, batch = 2113 / 4040 | |
| iter = 2113, cls_loss (cur) = 0.231616, cls_loss (avg) = 0.305358, lr = 0.010000 | |
| iter = 2113, accuracy (cur) = 0.880000 (all), 0.818182 (pos), 0.928571 (neg) | |
| iter = 2113, accuracy (avg) = 0.870245 (all), 0.877783 (pos), 0.862507 (neg) | |
| data reader: epoch = 0, batch = 2114 / 4040 | |
| iter = 2114, cls_loss (cur) = 0.247837, cls_loss (avg) = 0.304783, lr = 0.010000 | |
| iter = 2114, accuracy (cur) = 0.920000 (all), 0.952381 (pos), 0.896552 (neg) | |
| iter = 2114, accuracy (avg) = 0.870742 (all), 0.878529 (pos), 0.862847 (neg) | |
| data reader: epoch = 0, batch = 2115 / 4040 | |
| iter = 2115, cls_loss (cur) = 0.343601, cls_loss (avg) = 0.305171, lr = 0.010000 | |
| iter = 2115, accuracy (cur) = 0.880000 (all), 0.950000 (pos), 0.833333 (neg) | |
| iter = 2115, accuracy (avg) = 0.870835 (all), 0.879244 (pos), 0.862552 (neg) | |
| data reader: epoch = 0, batch = 2116 / 4040 | |
| iter = 2116, cls_loss (cur) = 0.284418, cls_loss (avg) = 0.304963, lr = 0.010000 | |
| iter = 2116, accuracy (cur) = 0.920000 (all), 0.875000 (pos), 0.961538 (neg) | |
| iter = 2116, accuracy (avg) = 0.871326 (all), 0.879201 (pos), 0.863542 (neg) | |
| data reader: epoch = 0, batch = 2117 / 4040 | |
| iter = 2117, cls_loss (cur) = 0.221632, cls_loss (avg) = 0.304130, lr = 0.010000 | |
| iter = 2117, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 2117, accuracy (avg) = 0.871613 (all), 0.879159 (pos), 0.864137 (neg) | |
| data reader: epoch = 0, batch = 2118 / 4040 | |
| iter = 2118, cls_loss (cur) = 0.454006, cls_loss (avg) = 0.305629, lr = 0.010000 | |
| iter = 2118, accuracy (cur) = 0.800000 (all), 0.884615 (pos), 0.708333 (neg) | |
| iter = 2118, accuracy (avg) = 0.870897 (all), 0.879214 (pos), 0.862579 (neg) | |
| data reader: epoch = 0, batch = 2119 / 4040 | |
| iter = 2119, cls_loss (cur) = 0.343930, cls_loss (avg) = 0.306012, lr = 0.010000 | |
| iter = 2119, accuracy (cur) = 0.860000 (all), 0.870968 (pos), 0.842105 (neg) | |
| iter = 2119, accuracy (avg) = 0.870788 (all), 0.879132 (pos), 0.862374 (neg) | |
| data reader: epoch = 0, batch = 2120 / 4040 | |
| iter = 2120, cls_loss (cur) = 0.456833, cls_loss (avg) = 0.307520, lr = 0.010000 | |
| iter = 2120, accuracy (cur) = 0.780000 (all), 0.740741 (pos), 0.826087 (neg) | |
| iter = 2120, accuracy (avg) = 0.869880 (all), 0.877748 (pos), 0.862012 (neg) | |
| data reader: epoch = 0, batch = 2121 / 4040 | |
| iter = 2121, cls_loss (cur) = 0.298526, cls_loss (avg) = 0.307430, lr = 0.010000 | |
| iter = 2121, accuracy (cur) = 0.880000 (all), 0.800000 (pos), 1.000000 (neg) | |
| iter = 2121, accuracy (avg) = 0.869981 (all), 0.876970 (pos), 0.863391 (neg) | |
| data reader: epoch = 0, batch = 2122 / 4040 | |
| iter = 2122, cls_loss (cur) = 0.238339, cls_loss (avg) = 0.306739, lr = 0.010000 | |
| iter = 2122, accuracy (cur) = 0.920000 (all), 0.906250 (pos), 0.944444 (neg) | |
| iter = 2122, accuracy (avg) = 0.870482 (all), 0.877263 (pos), 0.864202 (neg) | |
| data reader: epoch = 0, batch = 2123 / 4040 | |
| iter = 2123, cls_loss (cur) = 0.357838, cls_loss (avg) = 0.307250, lr = 0.010000 | |
| iter = 2123, accuracy (cur) = 0.820000 (all), 0.909091 (pos), 0.750000 (neg) | |
| iter = 2123, accuracy (avg) = 0.869977 (all), 0.877581 (pos), 0.863060 (neg) | |
| data reader: epoch = 0, batch = 2124 / 4040 | |
| iter = 2124, cls_loss (cur) = 0.319458, cls_loss (avg) = 0.307372, lr = 0.010000 | |
| iter = 2124, accuracy (cur) = 0.820000 (all), 0.769231 (pos), 0.875000 (neg) | |
| iter = 2124, accuracy (avg) = 0.869477 (all), 0.876498 (pos), 0.863179 (neg) | |
| data reader: epoch = 0, batch = 2125 / 4040 | |
| iter = 2125, cls_loss (cur) = 0.289637, cls_loss (avg) = 0.307195, lr = 0.010000 | |
| iter = 2125, accuracy (cur) = 0.840000 (all), 0.826087 (pos), 0.851852 (neg) | |
| iter = 2125, accuracy (avg) = 0.869182 (all), 0.875994 (pos), 0.863066 (neg) | |
| data reader: epoch = 0, batch = 2126 / 4040 | |
| iter = 2126, cls_loss (cur) = 0.599965, cls_loss (avg) = 0.310123, lr = 0.010000 | |
| iter = 2126, accuracy (cur) = 0.660000 (all), 0.724138 (pos), 0.571429 (neg) | |
| iter = 2126, accuracy (avg) = 0.867090 (all), 0.874475 (pos), 0.860150 (neg) | |
| data reader: epoch = 0, batch = 2127 / 4040 | |
| iter = 2127, cls_loss (cur) = 0.210138, cls_loss (avg) = 0.309123, lr = 0.010000 | |
| iter = 2127, accuracy (cur) = 0.920000 (all), 0.950000 (pos), 0.900000 (neg) | |
| iter = 2127, accuracy (avg) = 0.867620 (all), 0.875230 (pos), 0.860548 (neg) | |
| data reader: epoch = 0, batch = 2128 / 4040 | |
| iter = 2128, cls_loss (cur) = 0.350451, cls_loss (avg) = 0.309536, lr = 0.010000 | |
| iter = 2128, accuracy (cur) = 0.860000 (all), 0.862069 (pos), 0.857143 (neg) | |
| iter = 2128, accuracy (avg) = 0.867543 (all), 0.875099 (pos), 0.860514 (neg) | |
| data reader: epoch = 0, batch = 2129 / 4040 | |
| iter = 2129, cls_loss (cur) = 0.251876, cls_loss (avg) = 0.308959, lr = 0.010000 | |
| iter = 2129, accuracy (cur) = 0.920000 (all), 0.961538 (pos), 0.875000 (neg) | |
| iter = 2129, accuracy (avg) = 0.868068 (all), 0.875963 (pos), 0.860659 (neg) | |
| data reader: epoch = 0, batch = 2130 / 4040 | |
| iter = 2130, cls_loss (cur) = 0.298729, cls_loss (avg) = 0.308857, lr = 0.010000 | |
| iter = 2130, accuracy (cur) = 0.880000 (all), 0.913043 (pos), 0.851852 (neg) | |
| iter = 2130, accuracy (avg) = 0.868187 (all), 0.876334 (pos), 0.860571 (neg) | |
| data reader: epoch = 0, batch = 2131 / 4040 | |
| iter = 2131, cls_loss (cur) = 0.318574, cls_loss (avg) = 0.308954, lr = 0.010000 | |
| iter = 2131, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 2131, accuracy (avg) = 0.867905 (all), 0.875487 (pos), 0.860811 (neg) | |
| data reader: epoch = 0, batch = 2132 / 4040 | |
| iter = 2132, cls_loss (cur) = 0.223217, cls_loss (avg) = 0.308097, lr = 0.010000 | |
| iter = 2132, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 2132, accuracy (avg) = 0.868226 (all), 0.875732 (pos), 0.861203 (neg) | |
| data reader: epoch = 0, batch = 2133 / 4040 | |
| iter = 2133, cls_loss (cur) = 0.267096, cls_loss (avg) = 0.307687, lr = 0.010000 | |
| iter = 2133, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.869565 (neg) | |
| iter = 2133, accuracy (avg) = 0.868344 (all), 0.875864 (pos), 0.861287 (neg) | |
| data reader: epoch = 0, batch = 2134 / 4040 | |
| iter = 2134, cls_loss (cur) = 0.380059, cls_loss (avg) = 0.308411, lr = 0.010000 | |
| iter = 2134, accuracy (cur) = 0.800000 (all), 0.695652 (pos), 0.888889 (neg) | |
| iter = 2134, accuracy (avg) = 0.867661 (all), 0.874062 (pos), 0.861563 (neg) | |
| data reader: epoch = 0, batch = 2135 / 4040 | |
| iter = 2135, cls_loss (cur) = 0.402656, cls_loss (avg) = 0.309353, lr = 0.010000 | |
| iter = 2135, accuracy (cur) = 0.840000 (all), 0.909091 (pos), 0.785714 (neg) | |
| iter = 2135, accuracy (avg) = 0.867384 (all), 0.874412 (pos), 0.860804 (neg) | |
| data reader: epoch = 0, batch = 2136 / 4040 | |
| iter = 2136, cls_loss (cur) = 0.345347, cls_loss (avg) = 0.309713, lr = 0.010000 | |
| iter = 2136, accuracy (cur) = 0.800000 (all), 0.851852 (pos), 0.739130 (neg) | |
| iter = 2136, accuracy (avg) = 0.866710 (all), 0.874186 (pos), 0.859588 (neg) | |
| data reader: epoch = 0, batch = 2137 / 4040 | |
| iter = 2137, cls_loss (cur) = 0.367871, cls_loss (avg) = 0.310295, lr = 0.010000 | |
| iter = 2137, accuracy (cur) = 0.800000 (all), 0.821429 (pos), 0.772727 (neg) | |
| iter = 2137, accuracy (avg) = 0.866043 (all), 0.873659 (pos), 0.858719 (neg) | |
| data reader: epoch = 0, batch = 2138 / 4040 | |
| iter = 2138, cls_loss (cur) = 0.273213, cls_loss (avg) = 0.309924, lr = 0.010000 | |
| iter = 2138, accuracy (cur) = 0.880000 (all), 0.772727 (pos), 0.964286 (neg) | |
| iter = 2138, accuracy (avg) = 0.866183 (all), 0.872650 (pos), 0.859775 (neg) | |
| data reader: epoch = 0, batch = 2139 / 4040 | |
| iter = 2139, cls_loss (cur) = 0.286248, cls_loss (avg) = 0.309687, lr = 0.010000 | |
| iter = 2139, accuracy (cur) = 0.880000 (all), 0.947368 (pos), 0.838710 (neg) | |
| iter = 2139, accuracy (avg) = 0.866321 (all), 0.873397 (pos), 0.859564 (neg) | |
| data reader: epoch = 0, batch = 2140 / 4040 | |
| iter = 2140, cls_loss (cur) = 0.320818, cls_loss (avg) = 0.309798, lr = 0.010000 | |
| iter = 2140, accuracy (cur) = 0.840000 (all), 0.793103 (pos), 0.904762 (neg) | |
| iter = 2140, accuracy (avg) = 0.866058 (all), 0.872594 (pos), 0.860016 (neg) | |
| data reader: epoch = 0, batch = 2141 / 4040 | |
| iter = 2141, cls_loss (cur) = 0.314818, cls_loss (avg) = 0.309849, lr = 0.010000 | |
| iter = 2141, accuracy (cur) = 0.900000 (all), 0.888889 (pos), 0.913043 (neg) | |
| iter = 2141, accuracy (avg) = 0.866397 (all), 0.872757 (pos), 0.860546 (neg) | |
| data reader: epoch = 0, batch = 2142 / 4040 | |
| iter = 2142, cls_loss (cur) = 0.254038, cls_loss (avg) = 0.309290, lr = 0.010000 | |
| iter = 2142, accuracy (cur) = 0.880000 (all), 0.857143 (pos), 0.933333 (neg) | |
| iter = 2142, accuracy (avg) = 0.866533 (all), 0.872601 (pos), 0.861274 (neg) | |
| data reader: epoch = 0, batch = 2143 / 4040 | |
| iter = 2143, cls_loss (cur) = 0.274886, cls_loss (avg) = 0.308946, lr = 0.010000 | |
| iter = 2143, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.833333 (neg) | |
| iter = 2143, accuracy (avg) = 0.867068 (all), 0.873875 (pos), 0.860995 (neg) | |
| data reader: epoch = 0, batch = 2144 / 4040 | |
| iter = 2144, cls_loss (cur) = 0.249978, cls_loss (avg) = 0.308357, lr = 0.010000 | |
| iter = 2144, accuracy (cur) = 0.900000 (all), 0.884615 (pos), 0.916667 (neg) | |
| iter = 2144, accuracy (avg) = 0.867397 (all), 0.873982 (pos), 0.861551 (neg) | |
| data reader: epoch = 0, batch = 2145 / 4040 | |
| iter = 2145, cls_loss (cur) = 0.310980, cls_loss (avg) = 0.308383, lr = 0.010000 | |
| iter = 2145, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 2145, accuracy (avg) = 0.867123 (all), 0.874088 (pos), 0.860853 (neg) | |
| data reader: epoch = 0, batch = 2146 / 4040 | |
| iter = 2146, cls_loss (cur) = 0.266874, cls_loss (avg) = 0.307968, lr = 0.010000 | |
| iter = 2146, accuracy (cur) = 0.900000 (all), 0.863636 (pos), 0.928571 (neg) | |
| iter = 2146, accuracy (avg) = 0.867452 (all), 0.873984 (pos), 0.861530 (neg) | |
| data reader: epoch = 0, batch = 2147 / 4040 | |
| iter = 2147, cls_loss (cur) = 0.334042, cls_loss (avg) = 0.308229, lr = 0.010000 | |
| iter = 2147, accuracy (cur) = 0.840000 (all), 1.000000 (pos), 0.714286 (neg) | |
| iter = 2147, accuracy (avg) = 0.867177 (all), 0.875244 (pos), 0.860057 (neg) | |
| data reader: epoch = 0, batch = 2148 / 4040 | |
| iter = 2148, cls_loss (cur) = 0.351944, cls_loss (avg) = 0.308666, lr = 0.010000 | |
| iter = 2148, accuracy (cur) = 0.800000 (all), 0.913043 (pos), 0.703704 (neg) | |
| iter = 2148, accuracy (avg) = 0.866506 (all), 0.875622 (pos), 0.858494 (neg) | |
| data reader: epoch = 0, batch = 2149 / 4040 | |
| iter = 2149, cls_loss (cur) = 0.301115, cls_loss (avg) = 0.308590, lr = 0.010000 | |
| iter = 2149, accuracy (cur) = 0.880000 (all), 0.923077 (pos), 0.833333 (neg) | |
| iter = 2149, accuracy (avg) = 0.866640 (all), 0.876097 (pos), 0.858242 (neg) | |
| data reader: epoch = 0, batch = 2150 / 4040 | |
| iter = 2150, cls_loss (cur) = 0.219294, cls_loss (avg) = 0.307697, lr = 0.010000 | |
| iter = 2150, accuracy (cur) = 0.940000 (all), 0.935484 (pos), 0.947368 (neg) | |
| iter = 2150, accuracy (avg) = 0.867374 (all), 0.876690 (pos), 0.859134 (neg) | |
| data reader: epoch = 0, batch = 2151 / 4040 | |
| iter = 2151, cls_loss (cur) = 0.255200, cls_loss (avg) = 0.307172, lr = 0.010000 | |
| iter = 2151, accuracy (cur) = 0.940000 (all), 0.962963 (pos), 0.913043 (neg) | |
| iter = 2151, accuracy (avg) = 0.868100 (all), 0.877553 (pos), 0.859673 (neg) | |
| data reader: epoch = 0, batch = 2152 / 4040 | |
| iter = 2152, cls_loss (cur) = 0.315195, cls_loss (avg) = 0.307253, lr = 0.010000 | |
| iter = 2152, accuracy (cur) = 0.860000 (all), 0.789474 (pos), 0.903226 (neg) | |
| iter = 2152, accuracy (avg) = 0.868019 (all), 0.876672 (pos), 0.860108 (neg) | |
| data reader: epoch = 0, batch = 2153 / 4040 | |
| iter = 2153, cls_loss (cur) = 0.306098, cls_loss (avg) = 0.307241, lr = 0.010000 | |
| iter = 2153, accuracy (cur) = 0.840000 (all), 0.880000 (pos), 0.800000 (neg) | |
| iter = 2153, accuracy (avg) = 0.867739 (all), 0.876706 (pos), 0.859507 (neg) | |
| data reader: epoch = 0, batch = 2154 / 4040 | |
| iter = 2154, cls_loss (cur) = 0.391581, cls_loss (avg) = 0.308084, lr = 0.010000 | |
| iter = 2154, accuracy (cur) = 0.820000 (all), 0.772727 (pos), 0.857143 (neg) | |
| iter = 2154, accuracy (avg) = 0.867262 (all), 0.875666 (pos), 0.859483 (neg) | |
| data reader: epoch = 0, batch = 2155 / 4040 | |
| iter = 2155, cls_loss (cur) = 0.194811, cls_loss (avg) = 0.306952, lr = 0.010000 | |
| iter = 2155, accuracy (cur) = 0.980000 (all), 0.960000 (pos), 1.000000 (neg) | |
| iter = 2155, accuracy (avg) = 0.868389 (all), 0.876509 (pos), 0.860889 (neg) | |
| data reader: epoch = 0, batch = 2156 / 4040 | |
| iter = 2156, cls_loss (cur) = 0.203237, cls_loss (avg) = 0.305914, lr = 0.010000 | |
| iter = 2156, accuracy (cur) = 0.920000 (all), 0.958333 (pos), 0.884615 (neg) | |
| iter = 2156, accuracy (avg) = 0.868905 (all), 0.877327 (pos), 0.861126 (neg) | |
| data reader: epoch = 0, batch = 2157 / 4040 | |
| iter = 2157, cls_loss (cur) = 0.254307, cls_loss (avg) = 0.305398, lr = 0.010000 | |
| iter = 2157, accuracy (cur) = 0.860000 (all), 0.827586 (pos), 0.904762 (neg) | |
| iter = 2157, accuracy (avg) = 0.868816 (all), 0.876830 (pos), 0.861562 (neg) | |
| data reader: epoch = 0, batch = 2158 / 4040 | |
| iter = 2158, cls_loss (cur) = 0.304690, cls_loss (avg) = 0.305391, lr = 0.010000 | |
| iter = 2158, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 2158, accuracy (avg) = 0.868928 (all), 0.876323 (pos), 0.862206 (neg) | |
| data reader: epoch = 0, batch = 2159 / 4040 | |
| iter = 2159, cls_loss (cur) = 0.327302, cls_loss (avg) = 0.305610, lr = 0.010000 | |
| iter = 2159, accuracy (cur) = 0.820000 (all), 0.750000 (pos), 0.909091 (neg) | |
| iter = 2159, accuracy (avg) = 0.868439 (all), 0.875059 (pos), 0.862675 (neg) | |
| data reader: epoch = 0, batch = 2160 / 4040 | |
| iter = 2160, cls_loss (cur) = 0.373437, cls_loss (avg) = 0.306289, lr = 0.010000 | |
| iter = 2160, accuracy (cur) = 0.800000 (all), 0.761905 (pos), 0.827586 (neg) | |
| iter = 2160, accuracy (avg) = 0.867754 (all), 0.873928 (pos), 0.862324 (neg) | |
| data reader: epoch = 0, batch = 2161 / 4040 | |
| iter = 2161, cls_loss (cur) = 0.318712, cls_loss (avg) = 0.306413, lr = 0.010000 | |
| iter = 2161, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.863636 (neg) | |
| iter = 2161, accuracy (avg) = 0.867677 (all), 0.873760 (pos), 0.862337 (neg) | |
| data reader: epoch = 0, batch = 2162 / 4040 | |
| iter = 2162, cls_loss (cur) = 0.256957, cls_loss (avg) = 0.305918, lr = 0.010000 | |
| iter = 2162, accuracy (cur) = 0.920000 (all), 0.965517 (pos), 0.857143 (neg) | |
| iter = 2162, accuracy (avg) = 0.868200 (all), 0.874678 (pos), 0.862285 (neg) | |
| data reader: epoch = 0, batch = 2163 / 4040 | |
| iter = 2163, cls_loss (cur) = 0.428808, cls_loss (avg) = 0.307147, lr = 0.010000 | |
| iter = 2163, accuracy (cur) = 0.760000 (all), 0.863636 (pos), 0.678571 (neg) | |
| iter = 2163, accuracy (avg) = 0.867118 (all), 0.874567 (pos), 0.860448 (neg) | |
| data reader: epoch = 0, batch = 2164 / 4040 | |
| iter = 2164, cls_loss (cur) = 0.281676, cls_loss (avg) = 0.306893, lr = 0.010000 | |
| iter = 2164, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.818182 (neg) | |
| iter = 2164, accuracy (avg) = 0.866847 (all), 0.874393 (pos), 0.860025 (neg) | |
| data reader: epoch = 0, batch = 2165 / 4040 | |
| iter = 2165, cls_loss (cur) = 0.284822, cls_loss (avg) = 0.306672, lr = 0.010000 | |
| iter = 2165, accuracy (cur) = 0.900000 (all), 0.896552 (pos), 0.904762 (neg) | |
| iter = 2165, accuracy (avg) = 0.867178 (all), 0.874614 (pos), 0.860473 (neg) | |
| data reader: epoch = 0, batch = 2166 / 4040 | |
| iter = 2166, cls_loss (cur) = 0.272074, cls_loss (avg) = 0.306326, lr = 0.010000 | |
| iter = 2166, accuracy (cur) = 0.860000 (all), 0.892857 (pos), 0.818182 (neg) | |
| iter = 2166, accuracy (avg) = 0.867107 (all), 0.874797 (pos), 0.860050 (neg) | |
| data reader: epoch = 0, batch = 2167 / 4040 | |
| iter = 2167, cls_loss (cur) = 0.279346, cls_loss (avg) = 0.306056, lr = 0.010000 | |
| iter = 2167, accuracy (cur) = 0.900000 (all), 0.931034 (pos), 0.857143 (neg) | |
| iter = 2167, accuracy (avg) = 0.867436 (all), 0.875359 (pos), 0.860021 (neg) | |
| data reader: epoch = 0, batch = 2168 / 4040 | |
| iter = 2168, cls_loss (cur) = 0.289709, cls_loss (avg) = 0.305893, lr = 0.010000 | |
| iter = 2168, accuracy (cur) = 0.860000 (all), 0.923077 (pos), 0.791667 (neg) | |
| iter = 2168, accuracy (avg) = 0.867361 (all), 0.875836 (pos), 0.859337 (neg) | |
| data reader: epoch = 0, batch = 2169 / 4040 | |
| iter = 2169, cls_loss (cur) = 0.263824, cls_loss (avg) = 0.305472, lr = 0.010000 | |
| iter = 2169, accuracy (cur) = 0.880000 (all), 0.925926 (pos), 0.826087 (neg) | |
| iter = 2169, accuracy (avg) = 0.867488 (all), 0.876337 (pos), 0.859005 (neg) | |
| data reader: epoch = 0, batch = 2170 / 4040 | |
| iter = 2170, cls_loss (cur) = 0.292456, cls_loss (avg) = 0.305342, lr = 0.010000 | |
| iter = 2170, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 2170, accuracy (avg) = 0.867413 (all), 0.876092 (pos), 0.859110 (neg) | |
| data reader: epoch = 0, batch = 2171 / 4040 | |
| iter = 2171, cls_loss (cur) = 0.311291, cls_loss (avg) = 0.305401, lr = 0.010000 | |
| iter = 2171, accuracy (cur) = 0.820000 (all), 0.857143 (pos), 0.793103 (neg) | |
| iter = 2171, accuracy (avg) = 0.866939 (all), 0.875903 (pos), 0.858450 (neg) | |
| data reader: epoch = 0, batch = 2172 / 4040 | |
| iter = 2172, cls_loss (cur) = 0.240137, cls_loss (avg) = 0.304749, lr = 0.010000 | |
| iter = 2172, accuracy (cur) = 0.840000 (all), 0.884615 (pos), 0.791667 (neg) | |
| iter = 2172, accuracy (avg) = 0.866669 (all), 0.875990 (pos), 0.857782 (neg) | |
| data reader: epoch = 0, batch = 2173 / 4040 | |
| iter = 2173, cls_loss (cur) = 0.371517, cls_loss (avg) = 0.305416, lr = 0.010000 | |
| iter = 2173, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 2173, accuracy (avg) = 0.866203 (all), 0.874830 (pos), 0.858004 (neg) | |
| data reader: epoch = 0, batch = 2174 / 4040 | |
| iter = 2174, cls_loss (cur) = 0.291973, cls_loss (avg) = 0.305282, lr = 0.010000 | |
| iter = 2174, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 2174, accuracy (avg) = 0.866340 (all), 0.874543 (pos), 0.858591 (neg) | |
| data reader: epoch = 0, batch = 2175 / 4040 | |
| iter = 2175, cls_loss (cur) = 0.347896, cls_loss (avg) = 0.305708, lr = 0.010000 | |
| iter = 2175, accuracy (cur) = 0.880000 (all), 0.950000 (pos), 0.833333 (neg) | |
| iter = 2175, accuracy (avg) = 0.866477 (all), 0.875298 (pos), 0.858338 (neg) | |
| data reader: epoch = 0, batch = 2176 / 4040 | |
| iter = 2176, cls_loss (cur) = 0.222059, cls_loss (avg) = 0.304872, lr = 0.010000 | |
| iter = 2176, accuracy (cur) = 0.940000 (all), 0.916667 (pos), 0.961538 (neg) | |
| iter = 2176, accuracy (avg) = 0.867212 (all), 0.875712 (pos), 0.859370 (neg) | |
| data reader: epoch = 0, batch = 2177 / 4040 | |
| iter = 2177, cls_loss (cur) = 0.223573, cls_loss (avg) = 0.304059, lr = 0.010000 | |
| iter = 2177, accuracy (cur) = 0.900000 (all), 0.884615 (pos), 0.916667 (neg) | |
| iter = 2177, accuracy (avg) = 0.867540 (all), 0.875801 (pos), 0.859943 (neg) | |
| data reader: epoch = 0, batch = 2178 / 4040 | |
| iter = 2178, cls_loss (cur) = 0.295304, cls_loss (avg) = 0.303971, lr = 0.010000 | |
| iter = 2178, accuracy (cur) = 0.900000 (all), 0.920000 (pos), 0.880000 (neg) | |
| iter = 2178, accuracy (avg) = 0.867865 (all), 0.876243 (pos), 0.860144 (neg) | |
| data reader: epoch = 0, batch = 2179 / 4040 | |
| iter = 2179, cls_loss (cur) = 0.316195, cls_loss (avg) = 0.304093, lr = 0.010000 | |
| iter = 2179, accuracy (cur) = 0.880000 (all), 0.911765 (pos), 0.812500 (neg) | |
| iter = 2179, accuracy (avg) = 0.867986 (all), 0.876598 (pos), 0.859668 (neg) | |
| data reader: epoch = 0, batch = 2180 / 4040 | |
| iter = 2180, cls_loss (cur) = 0.353315, cls_loss (avg) = 0.304585, lr = 0.010000 | |
| iter = 2180, accuracy (cur) = 0.820000 (all), 0.888889 (pos), 0.739130 (neg) | |
| iter = 2180, accuracy (avg) = 0.867506 (all), 0.876721 (pos), 0.858462 (neg) | |
| data reader: epoch = 0, batch = 2181 / 4040 | |
| iter = 2181, cls_loss (cur) = 0.212542, cls_loss (avg) = 0.303665, lr = 0.010000 | |
| iter = 2181, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.909091 (neg) | |
| iter = 2181, accuracy (avg) = 0.868431 (all), 0.877954 (pos), 0.858968 (neg) | |
| data reader: epoch = 0, batch = 2182 / 4040 | |
| iter = 2182, cls_loss (cur) = 0.316935, cls_loss (avg) = 0.303798, lr = 0.010000 | |
| iter = 2182, accuracy (cur) = 0.920000 (all), 0.909091 (pos), 0.941176 (neg) | |
| iter = 2182, accuracy (avg) = 0.868947 (all), 0.878265 (pos), 0.859791 (neg) | |
| data reader: epoch = 0, batch = 2183 / 4040 | |
| iter = 2183, cls_loss (cur) = 0.385256, cls_loss (avg) = 0.304612, lr = 0.010000 | |
| iter = 2183, accuracy (cur) = 0.840000 (all), 0.785714 (pos), 0.909091 (neg) | |
| iter = 2183, accuracy (avg) = 0.868657 (all), 0.877340 (pos), 0.860284 (neg) | |
| data reader: epoch = 0, batch = 2184 / 4040 | |
| iter = 2184, cls_loss (cur) = 0.334952, cls_loss (avg) = 0.304916, lr = 0.010000 | |
| iter = 2184, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 2184, accuracy (avg) = 0.868371 (all), 0.876966 (pos), 0.860081 (neg) | |
| data reader: epoch = 0, batch = 2185 / 4040 | |
| iter = 2185, cls_loss (cur) = 0.251452, cls_loss (avg) = 0.304381, lr = 0.010000 | |
| iter = 2185, accuracy (cur) = 0.900000 (all), 0.880000 (pos), 0.920000 (neg) | |
| iter = 2185, accuracy (avg) = 0.868687 (all), 0.876996 (pos), 0.860680 (neg) | |
| data reader: epoch = 0, batch = 2186 / 4040 | |
| iter = 2186, cls_loss (cur) = 0.252523, cls_loss (avg) = 0.303862, lr = 0.010000 | |
| iter = 2186, accuracy (cur) = 0.920000 (all), 0.869565 (pos), 0.962963 (neg) | |
| iter = 2186, accuracy (avg) = 0.869200 (all), 0.876922 (pos), 0.861703 (neg) | |
| data reader: epoch = 0, batch = 2187 / 4040 | |
| iter = 2187, cls_loss (cur) = 0.385091, cls_loss (avg) = 0.304675, lr = 0.010000 | |
| iter = 2187, accuracy (cur) = 0.840000 (all), 0.956522 (pos), 0.740741 (neg) | |
| iter = 2187, accuracy (avg) = 0.868908 (all), 0.877718 (pos), 0.860493 (neg) | |
| data reader: epoch = 0, batch = 2188 / 4040 | |
| iter = 2188, cls_loss (cur) = 0.381160, cls_loss (avg) = 0.305440, lr = 0.010000 | |
| iter = 2188, accuracy (cur) = 0.800000 (all), 0.869565 (pos), 0.740741 (neg) | |
| iter = 2188, accuracy (avg) = 0.868219 (all), 0.877637 (pos), 0.859296 (neg) | |
| data reader: epoch = 0, batch = 2189 / 4040 | |
| iter = 2189, cls_loss (cur) = 0.345640, cls_loss (avg) = 0.305842, lr = 0.010000 | |
| iter = 2189, accuracy (cur) = 0.800000 (all), 0.772727 (pos), 0.821429 (neg) | |
| iter = 2189, accuracy (avg) = 0.867537 (all), 0.876588 (pos), 0.858917 (neg) | |
| data reader: epoch = 0, batch = 2190 / 4040 | |
| iter = 2190, cls_loss (cur) = 0.254389, cls_loss (avg) = 0.305327, lr = 0.010000 | |
| iter = 2190, accuracy (cur) = 0.920000 (all), 0.958333 (pos), 0.884615 (neg) | |
| iter = 2190, accuracy (avg) = 0.868062 (all), 0.877405 (pos), 0.859174 (neg) | |
| data reader: epoch = 0, batch = 2191 / 4040 | |
| iter = 2191, cls_loss (cur) = 0.313760, cls_loss (avg) = 0.305411, lr = 0.010000 | |
| iter = 2191, accuracy (cur) = 0.820000 (all), 0.909091 (pos), 0.750000 (neg) | |
| iter = 2191, accuracy (avg) = 0.867581 (all), 0.877722 (pos), 0.858082 (neg) | |
| data reader: epoch = 0, batch = 2192 / 4040 | |
| iter = 2192, cls_loss (cur) = 0.305654, cls_loss (avg) = 0.305414, lr = 0.010000 | |
| iter = 2192, accuracy (cur) = 0.880000 (all), 0.761905 (pos), 0.965517 (neg) | |
| iter = 2192, accuracy (avg) = 0.867705 (all), 0.876564 (pos), 0.859157 (neg) | |
| data reader: epoch = 0, batch = 2193 / 4040 | |
| iter = 2193, cls_loss (cur) = 0.358752, cls_loss (avg) = 0.305947, lr = 0.010000 | |
| iter = 2193, accuracy (cur) = 0.840000 (all), 0.750000 (pos), 0.923077 (neg) | |
| iter = 2193, accuracy (avg) = 0.867428 (all), 0.875298 (pos), 0.859796 (neg) | |
| data reader: epoch = 0, batch = 2194 / 4040 | |
| iter = 2194, cls_loss (cur) = 0.261786, cls_loss (avg) = 0.305506, lr = 0.010000 | |
| iter = 2194, accuracy (cur) = 0.920000 (all), 0.956522 (pos), 0.888889 (neg) | |
| iter = 2194, accuracy (avg) = 0.867954 (all), 0.876110 (pos), 0.860087 (neg) | |
| data reader: epoch = 0, batch = 2195 / 4040 | |
| iter = 2195, cls_loss (cur) = 0.259846, cls_loss (avg) = 0.305049, lr = 0.010000 | |
| iter = 2195, accuracy (cur) = 0.940000 (all), 0.954545 (pos), 0.928571 (neg) | |
| iter = 2195, accuracy (avg) = 0.868674 (all), 0.876895 (pos), 0.860772 (neg) | |
| data reader: epoch = 0, batch = 2196 / 4040 | |
| iter = 2196, cls_loss (cur) = 0.319650, cls_loss (avg) = 0.305195, lr = 0.010000 | |
| iter = 2196, accuracy (cur) = 0.860000 (all), 0.681818 (pos), 1.000000 (neg) | |
| iter = 2196, accuracy (avg) = 0.868588 (all), 0.874944 (pos), 0.862164 (neg) | |
| data reader: epoch = 0, batch = 2197 / 4040 | |
| iter = 2197, cls_loss (cur) = 0.314361, cls_loss (avg) = 0.305287, lr = 0.010000 | |
| iter = 2197, accuracy (cur) = 0.840000 (all), 0.761905 (pos), 0.896552 (neg) | |
| iter = 2197, accuracy (avg) = 0.868302 (all), 0.873813 (pos), 0.862508 (neg) | |
| data reader: epoch = 0, batch = 2198 / 4040 | |
| iter = 2198, cls_loss (cur) = 0.279075, cls_loss (avg) = 0.305025, lr = 0.010000 | |
| iter = 2198, accuracy (cur) = 0.900000 (all), 0.866667 (pos), 0.950000 (neg) | |
| iter = 2198, accuracy (avg) = 0.868619 (all), 0.873742 (pos), 0.863383 (neg) | |
| data reader: epoch = 0, batch = 2199 / 4040 | |
| iter = 2199, cls_loss (cur) = 0.354961, cls_loss (avg) = 0.305524, lr = 0.010000 | |
| iter = 2199, accuracy (cur) = 0.820000 (all), 0.793103 (pos), 0.857143 (neg) | |
| iter = 2199, accuracy (avg) = 0.868133 (all), 0.872936 (pos), 0.863320 (neg) | |
| data reader: epoch = 0, batch = 2200 / 4040 | |
| iter = 2200, cls_loss (cur) = 0.406565, cls_loss (avg) = 0.306534, lr = 0.010000 | |
| iter = 2200, accuracy (cur) = 0.840000 (all), 0.840000 (pos), 0.840000 (neg) | |
| iter = 2200, accuracy (avg) = 0.867851 (all), 0.872606 (pos), 0.863087 (neg) | |
| data reader: epoch = 0, batch = 2201 / 4040 | |
| iter = 2201, cls_loss (cur) = 0.211363, cls_loss (avg) = 0.305583, lr = 0.010000 | |
| iter = 2201, accuracy (cur) = 0.940000 (all), 0.958333 (pos), 0.923077 (neg) | |
| iter = 2201, accuracy (avg) = 0.868573 (all), 0.873464 (pos), 0.863687 (neg) | |
| data reader: epoch = 0, batch = 2202 / 4040 | |
| iter = 2202, cls_loss (cur) = 0.233706, cls_loss (avg) = 0.304864, lr = 0.010000 | |
| iter = 2202, accuracy (cur) = 0.940000 (all), 0.956522 (pos), 0.925926 (neg) | |
| iter = 2202, accuracy (avg) = 0.869287 (all), 0.874294 (pos), 0.864309 (neg) | |
| data reader: epoch = 0, batch = 2203 / 4040 | |
| iter = 2203, cls_loss (cur) = 0.284807, cls_loss (avg) = 0.304663, lr = 0.010000 | |
| iter = 2203, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 2203, accuracy (avg) = 0.869594 (all), 0.874551 (pos), 0.864666 (neg) | |
| data reader: epoch = 0, batch = 2204 / 4040 | |
| iter = 2204, cls_loss (cur) = 0.204106, cls_loss (avg) = 0.303658, lr = 0.010000 | |
| iter = 2204, accuracy (cur) = 0.940000 (all), 0.960000 (pos), 0.920000 (neg) | |
| iter = 2204, accuracy (avg) = 0.870298 (all), 0.875406 (pos), 0.865220 (neg) | |
| data reader: epoch = 0, batch = 2205 / 4040 | |
| iter = 2205, cls_loss (cur) = 0.291898, cls_loss (avg) = 0.303540, lr = 0.010000 | |
| iter = 2205, accuracy (cur) = 0.860000 (all), 0.925926 (pos), 0.782609 (neg) | |
| iter = 2205, accuracy (avg) = 0.870195 (all), 0.875911 (pos), 0.864393 (neg) | |
| data reader: epoch = 0, batch = 2206 / 4040 | |
| iter = 2206, cls_loss (cur) = 0.495485, cls_loss (avg) = 0.305460, lr = 0.010000 | |
| iter = 2206, accuracy (cur) = 0.820000 (all), 0.900000 (pos), 0.766667 (neg) | |
| iter = 2206, accuracy (avg) = 0.869693 (all), 0.876152 (pos), 0.863416 (neg) | |
| data reader: epoch = 0, batch = 2207 / 4040 | |
| iter = 2207, cls_loss (cur) = 0.323375, cls_loss (avg) = 0.305639, lr = 0.010000 | |
| iter = 2207, accuracy (cur) = 0.860000 (all), 0.950000 (pos), 0.800000 (neg) | |
| iter = 2207, accuracy (avg) = 0.869596 (all), 0.876890 (pos), 0.862782 (neg) | |
| data reader: epoch = 0, batch = 2208 / 4040 | |
| iter = 2208, cls_loss (cur) = 0.393243, cls_loss (avg) = 0.306515, lr = 0.010000 | |
| iter = 2208, accuracy (cur) = 0.880000 (all), 0.960000 (pos), 0.800000 (neg) | |
| iter = 2208, accuracy (avg) = 0.869700 (all), 0.877721 (pos), 0.862154 (neg) | |
| data reader: epoch = 0, batch = 2209 / 4040 | |
| iter = 2209, cls_loss (cur) = 0.241684, cls_loss (avg) = 0.305866, lr = 0.010000 | |
| iter = 2209, accuracy (cur) = 0.920000 (all), 0.931034 (pos), 0.904762 (neg) | |
| iter = 2209, accuracy (avg) = 0.870203 (all), 0.878254 (pos), 0.862580 (neg) | |
| data reader: epoch = 0, batch = 2210 / 4040 | |
| iter = 2210, cls_loss (cur) = 0.208975, cls_loss (avg) = 0.304898, lr = 0.010000 | |
| iter = 2210, accuracy (cur) = 0.920000 (all), 0.892857 (pos), 0.954545 (neg) | |
| iter = 2210, accuracy (avg) = 0.870701 (all), 0.878400 (pos), 0.863500 (neg) | |
| data reader: epoch = 0, batch = 2211 / 4040 | |
| iter = 2211, cls_loss (cur) = 0.317319, cls_loss (avg) = 0.305022, lr = 0.010000 | |
| iter = 2211, accuracy (cur) = 0.860000 (all), 0.827586 (pos), 0.904762 (neg) | |
| iter = 2211, accuracy (avg) = 0.870594 (all), 0.877892 (pos), 0.863913 (neg) | |
| data reader: epoch = 0, batch = 2212 / 4040 | |
| iter = 2212, cls_loss (cur) = 0.423110, cls_loss (avg) = 0.306203, lr = 0.010000 | |
| iter = 2212, accuracy (cur) = 0.840000 (all), 0.791667 (pos), 0.884615 (neg) | |
| iter = 2212, accuracy (avg) = 0.870288 (all), 0.877030 (pos), 0.864120 (neg) | |
| data reader: epoch = 0, batch = 2213 / 4040 | |
| iter = 2213, cls_loss (cur) = 0.258215, cls_loss (avg) = 0.305723, lr = 0.010000 | |
| iter = 2213, accuracy (cur) = 0.840000 (all), 0.909091 (pos), 0.785714 (neg) | |
| iter = 2213, accuracy (avg) = 0.869985 (all), 0.877351 (pos), 0.863336 (neg) | |
| data reader: epoch = 0, batch = 2214 / 4040 | |
| iter = 2214, cls_loss (cur) = 0.271259, cls_loss (avg) = 0.305378, lr = 0.010000 | |
| iter = 2214, accuracy (cur) = 0.900000 (all), 0.857143 (pos), 0.954545 (neg) | |
| iter = 2214, accuracy (avg) = 0.870286 (all), 0.877149 (pos), 0.864248 (neg) | |
| data reader: epoch = 0, batch = 2215 / 4040 | |
| iter = 2215, cls_loss (cur) = 0.340938, cls_loss (avg) = 0.305734, lr = 0.010000 | |
| iter = 2215, accuracy (cur) = 0.840000 (all), 0.870968 (pos), 0.789474 (neg) | |
| iter = 2215, accuracy (avg) = 0.869983 (all), 0.877087 (pos), 0.863500 (neg) | |
| data reader: epoch = 0, batch = 2216 / 4040 | |
| iter = 2216, cls_loss (cur) = 0.390705, cls_loss (avg) = 0.306583, lr = 0.010000 | |
| iter = 2216, accuracy (cur) = 0.780000 (all), 0.777778 (pos), 0.782609 (neg) | |
| iter = 2216, accuracy (avg) = 0.869083 (all), 0.876094 (pos), 0.862691 (neg) | |
| data reader: epoch = 0, batch = 2217 / 4040 | |
| iter = 2217, cls_loss (cur) = 0.385910, cls_loss (avg) = 0.307377, lr = 0.010000 | |
| iter = 2217, accuracy (cur) = 0.860000 (all), 0.964286 (pos), 0.727273 (neg) | |
| iter = 2217, accuracy (avg) = 0.868992 (all), 0.876976 (pos), 0.861337 (neg) | |
| data reader: epoch = 0, batch = 2218 / 4040 | |
| iter = 2218, cls_loss (cur) = 0.310093, cls_loss (avg) = 0.307404, lr = 0.010000 | |
| iter = 2218, accuracy (cur) = 0.820000 (all), 0.956522 (pos), 0.703704 (neg) | |
| iter = 2218, accuracy (avg) = 0.868502 (all), 0.877771 (pos), 0.859760 (neg) | |
| data reader: epoch = 0, batch = 2219 / 4040 | |
| iter = 2219, cls_loss (cur) = 0.296799, cls_loss (avg) = 0.307298, lr = 0.010000 | |
| iter = 2219, accuracy (cur) = 0.900000 (all), 0.965517 (pos), 0.809524 (neg) | |
| iter = 2219, accuracy (avg) = 0.868817 (all), 0.878649 (pos), 0.859258 (neg) | |
| data reader: epoch = 0, batch = 2220 / 4040 | |
| iter = 2220, cls_loss (cur) = 0.230705, cls_loss (avg) = 0.306532, lr = 0.010000 | |
| iter = 2220, accuracy (cur) = 0.920000 (all), 0.958333 (pos), 0.884615 (neg) | |
| iter = 2220, accuracy (avg) = 0.869329 (all), 0.879445 (pos), 0.859512 (neg) | |
| data reader: epoch = 0, batch = 2221 / 4040 | |
| iter = 2221, cls_loss (cur) = 0.358889, cls_loss (avg) = 0.307055, lr = 0.010000 | |
| iter = 2221, accuracy (cur) = 0.820000 (all), 0.818182 (pos), 0.821429 (neg) | |
| iter = 2221, accuracy (avg) = 0.868836 (all), 0.878833 (pos), 0.859131 (neg) | |
| data reader: epoch = 0, batch = 2222 / 4040 | |
| iter = 2222, cls_loss (cur) = 0.315970, cls_loss (avg) = 0.307145, lr = 0.010000 | |
| iter = 2222, accuracy (cur) = 0.840000 (all), 0.842105 (pos), 0.838710 (neg) | |
| iter = 2222, accuracy (avg) = 0.868547 (all), 0.878466 (pos), 0.858927 (neg) | |
| data reader: epoch = 0, batch = 2223 / 4040 | |
| iter = 2223, cls_loss (cur) = 0.283718, cls_loss (avg) = 0.306910, lr = 0.010000 | |
| iter = 2223, accuracy (cur) = 0.920000 (all), 0.925926 (pos), 0.913043 (neg) | |
| iter = 2223, accuracy (avg) = 0.869062 (all), 0.878940 (pos), 0.859468 (neg) | |
| data reader: epoch = 0, batch = 2224 / 4040 | |
| iter = 2224, cls_loss (cur) = 0.282519, cls_loss (avg) = 0.306666, lr = 0.010000 | |
| iter = 2224, accuracy (cur) = 0.900000 (all), 0.904762 (pos), 0.896552 (neg) | |
| iter = 2224, accuracy (avg) = 0.869371 (all), 0.879198 (pos), 0.859839 (neg) | |
| data reader: epoch = 0, batch = 2225 / 4040 | |
| iter = 2225, cls_loss (cur) = 0.300465, cls_loss (avg) = 0.306604, lr = 0.010000 | |
| iter = 2225, accuracy (cur) = 0.880000 (all), 0.791667 (pos), 0.961538 (neg) | |
| iter = 2225, accuracy (avg) = 0.869477 (all), 0.878323 (pos), 0.860856 (neg) | |
| data reader: epoch = 0, batch = 2226 / 4040 | |
| iter = 2226, cls_loss (cur) = 0.224339, cls_loss (avg) = 0.305782, lr = 0.010000 | |
| iter = 2226, accuracy (cur) = 0.960000 (all), 0.958333 (pos), 0.961538 (neg) | |
| iter = 2226, accuracy (avg) = 0.870383 (all), 0.879123 (pos), 0.861862 (neg) | |
| data reader: epoch = 0, batch = 2227 / 4040 | |
| iter = 2227, cls_loss (cur) = 0.207494, cls_loss (avg) = 0.304799, lr = 0.010000 | |
| iter = 2227, accuracy (cur) = 0.900000 (all), 0.900000 (pos), 0.900000 (neg) | |
| iter = 2227, accuracy (avg) = 0.870679 (all), 0.879332 (pos), 0.862244 (neg) | |
| data reader: epoch = 0, batch = 2228 / 4040 | |
| iter = 2228, cls_loss (cur) = 0.394657, cls_loss (avg) = 0.305697, lr = 0.010000 | |
| iter = 2228, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 2228, accuracy (avg) = 0.870172 (all), 0.878455 (pos), 0.862083 (neg) | |
| data reader: epoch = 0, batch = 2229 / 4040 | |
| iter = 2229, cls_loss (cur) = 0.308154, cls_loss (avg) = 0.305722, lr = 0.010000 | |
| iter = 2229, accuracy (cur) = 0.900000 (all), 0.878788 (pos), 0.941176 (neg) | |
| iter = 2229, accuracy (avg) = 0.870470 (all), 0.878459 (pos), 0.862874 (neg) | |
| data reader: epoch = 0, batch = 2230 / 4040 | |
| iter = 2230, cls_loss (cur) = 0.290761, cls_loss (avg) = 0.305572, lr = 0.010000 | |
| iter = 2230, accuracy (cur) = 0.880000 (all), 0.809524 (pos), 0.931034 (neg) | |
| iter = 2230, accuracy (avg) = 0.870566 (all), 0.877769 (pos), 0.863555 (neg) | |
| data reader: epoch = 0, batch = 2231 / 4040 | |
| iter = 2231, cls_loss (cur) = 0.494246, cls_loss (avg) = 0.307459, lr = 0.010000 | |
| iter = 2231, accuracy (cur) = 0.760000 (all), 0.645161 (pos), 0.947368 (neg) | |
| iter = 2231, accuracy (avg) = 0.869460 (all), 0.875443 (pos), 0.864394 (neg) | |
| data reader: epoch = 0, batch = 2232 / 4040 | |
| iter = 2232, cls_loss (cur) = 0.193422, cls_loss (avg) = 0.306319, lr = 0.010000 | |
| iter = 2232, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 2232, accuracy (avg) = 0.869765 (all), 0.875150 (pos), 0.865333 (neg) | |
| data reader: epoch = 0, batch = 2233 / 4040 | |
| iter = 2233, cls_loss (cur) = 0.294553, cls_loss (avg) = 0.306201, lr = 0.010000 | |
| iter = 2233, accuracy (cur) = 0.880000 (all), 0.952381 (pos), 0.827586 (neg) | |
| iter = 2233, accuracy (avg) = 0.869868 (all), 0.875923 (pos), 0.864956 (neg) | |
| data reader: epoch = 0, batch = 2234 / 4040 | |
| iter = 2234, cls_loss (cur) = 0.231972, cls_loss (avg) = 0.305459, lr = 0.010000 | |
| iter = 2234, accuracy (cur) = 0.900000 (all), 0.923077 (pos), 0.875000 (neg) | |
| iter = 2234, accuracy (avg) = 0.870169 (all), 0.876394 (pos), 0.865056 (neg) | |
| data reader: epoch = 0, batch = 2235 / 4040 | |
| iter = 2235, cls_loss (cur) = 0.434336, cls_loss (avg) = 0.306748, lr = 0.010000 | |
| iter = 2235, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 2235, accuracy (avg) = 0.870067 (all), 0.876830 (pos), 0.864405 (neg) | |
| data reader: epoch = 0, batch = 2236 / 4040 | |
| iter = 2236, cls_loss (cur) = 0.327522, cls_loss (avg) = 0.306955, lr = 0.010000 | |
| iter = 2236, accuracy (cur) = 0.900000 (all), 0.961538 (pos), 0.833333 (neg) | |
| iter = 2236, accuracy (avg) = 0.870367 (all), 0.877677 (pos), 0.864095 (neg) | |
| data reader: epoch = 0, batch = 2237 / 4040 | |
| iter = 2237, cls_loss (cur) = 0.402938, cls_loss (avg) = 0.307915, lr = 0.010000 | |
| iter = 2237, accuracy (cur) = 0.820000 (all), 0.916667 (pos), 0.730769 (neg) | |
| iter = 2237, accuracy (avg) = 0.869863 (all), 0.878067 (pos), 0.862761 (neg) | |
| data reader: epoch = 0, batch = 2238 / 4040 | |
| iter = 2238, cls_loss (cur) = 0.167301, cls_loss (avg) = 0.306509, lr = 0.010000 | |
| iter = 2238, accuracy (cur) = 0.960000 (all), 0.956522 (pos), 0.962963 (neg) | |
| iter = 2238, accuracy (avg) = 0.870764 (all), 0.878852 (pos), 0.863763 (neg) | |
| data reader: epoch = 0, batch = 2239 / 4040 | |
| iter = 2239, cls_loss (cur) = 0.299525, cls_loss (avg) = 0.306439, lr = 0.010000 | |
| iter = 2239, accuracy (cur) = 0.860000 (all), 0.857143 (pos), 0.862069 (neg) | |
| iter = 2239, accuracy (avg) = 0.870657 (all), 0.878635 (pos), 0.863746 (neg) | |
| data reader: epoch = 0, batch = 2240 / 4040 | |
| iter = 2240, cls_loss (cur) = 0.247045, cls_loss (avg) = 0.305845, lr = 0.010000 | |
| iter = 2240, accuracy (cur) = 0.900000 (all), 0.846154 (pos), 0.958333 (neg) | |
| iter = 2240, accuracy (avg) = 0.870950 (all), 0.878310 (pos), 0.864692 (neg) | |
| data reader: epoch = 0, batch = 2241 / 4040 | |
| iter = 2241, cls_loss (cur) = 0.273490, cls_loss (avg) = 0.305522, lr = 0.010000 | |
| iter = 2241, accuracy (cur) = 0.860000 (all), 0.851852 (pos), 0.869565 (neg) | |
| iter = 2241, accuracy (avg) = 0.870841 (all), 0.878045 (pos), 0.864741 (neg) | |
| data reader: epoch = 0, batch = 2242 / 4040 | |
| iter = 2242, cls_loss (cur) = 0.230957, cls_loss (avg) = 0.304776, lr = 0.010000 | |
| iter = 2242, accuracy (cur) = 0.900000 (all), 0.875000 (pos), 0.923077 (neg) | |
| iter = 2242, accuracy (avg) = 0.871132 (all), 0.878015 (pos), 0.865324 (neg) | |
| data reader: epoch = 0, batch = 2243 / 4040 | |
| iter = 2243, cls_loss (cur) = 0.293703, cls_loss (avg) = 0.304665, lr = 0.010000 | |
| iter = 2243, accuracy (cur) = 0.900000 (all), 0.906250 (pos), 0.888889 (neg) | |
| iter = 2243, accuracy (avg) = 0.871421 (all), 0.878297 (pos), 0.865560 (neg) | |
| data reader: epoch = 0, batch = 2244 / 4040 | |
| iter = 2244, cls_loss (cur) = 0.371398, cls_loss (avg) = 0.305333, lr = 0.010000 | |
| iter = 2244, accuracy (cur) = 0.820000 (all), 0.833333 (pos), 0.807692 (neg) | |
| iter = 2244, accuracy (avg) = 0.870907 (all), 0.877847 (pos), 0.864981 (neg) | |
| data reader: epoch = 0, batch = 2245 / 4040 | |
| iter = 2245, cls_loss (cur) = 0.257541, cls_loss (avg) = 0.304855, lr = 0.010000 | |
| iter = 2245, accuracy (cur) = 0.900000 (all), 0.928571 (pos), 0.863636 (neg) | |
| iter = 2245, accuracy (avg) = 0.871198 (all), 0.878355 (pos), 0.864968 (neg) | |
| data reader: epoch = 0, batch = 2246 / 4040 | |
| iter = 2246, cls_loss (cur) = 0.223194, cls_loss (avg) = 0.304038, lr = 0.010000 | |
| iter = 2246, accuracy (cur) = 0.940000 (all), 0.939394 (pos), 0.941176 (neg) | |
| iter = 2246, accuracy (avg) = 0.871886 (all), 0.878965 (pos), 0.865730 (neg) | |
| data reader: epoch = 0, batch = 2247 / 4040 | |
| iter = 2247, cls_loss (cur) = 0.295162, cls_loss (avg) = 0.303949, lr = 0.010000 | |
| iter = 2247, accuracy (cur) = 0.880000 (all), 0.840000 (pos), 0.920000 (neg) | |
| iter = 2247, accuracy (avg) = 0.871967 (all), 0.878575 (pos), 0.866273 (neg) | |
| data reader: epoch = 0, batch = 2248 / 4040 | |
| iter = 2248, cls_loss (cur) = 0.270611, cls_loss (avg) = 0.303616, lr = 0.010000 | |
| iter = 2248, accuracy (cur) = 0.840000 (all), 0.875000 (pos), 0.807692 (neg) | |
| iter = 2248, accuracy (avg) = 0.871647 (all), 0.878540 (pos), 0.865687 (neg) | |
| data reader: epoch = 0, batch = 2249 / 4040 | |
| iter = 2249, cls_loss (cur) = 0.312473, cls_loss (avg) = 0.303705, lr = 0.010000 | |
| iter = 2249, accuracy (cur) = 0.860000 (all), 0.823529 (pos), 0.937500 (neg) | |
| iter = 2249, accuracy (avg) = 0.871531 (all), 0.877990 (pos), 0.866405 (neg) | |
| data reader: epoch = 0, batch = 2250 / 4040 | |
| iter = 2250, cls_loss (cur) = 0.376012, cls_loss (avg) = 0.304428, lr = 0.010000 | |
| iter = 2250, accuracy (cur) = 0.820000 (all), 0.913043 (pos), 0.740741 (neg) | |
| iter = 2250, accuracy (avg) = 0.871015 (all), 0.878340 (pos), 0.865148 (neg) | |
| data reader: epoch = 0, batch = 2251 / 4040 | |
| iter = 2251, cls_loss (cur) = 0.321720, cls_loss (avg) = 0.304601, lr = 0.010000 | |
| iter = 2251, accuracy (cur) = 0.820000 (all), 0.920000 (pos), 0.720000 (neg) | |
| iter = 2251, accuracy (avg) = 0.870505 (all), 0.878757 (pos), 0.863697 (neg) | |
| data reader: epoch = 0, batch = 2252 / 4040 | |
| iter = 2252, cls_loss (cur) = 0.325670, cls_loss (avg) = 0.304811, lr = 0.010000 | |
| iter = 2252, accuracy (cur) = 0.860000 (all), 0.880000 (pos), 0.840000 (neg) | |
| iter = 2252, accuracy (avg) = 0.870400 (all), 0.878769 (pos), 0.863460 (neg) | |
| data reader: epoch = 0, batch = 2253 / 4040 | |
| iter = 2253, cls_loss (cur) = 0.358893, cls_loss (avg) = 0.305352, lr = 0.010000 | |
| iter = 2253, accuracy (cur) = 0.840000 (all), 0.935484 (pos), 0.684211 (neg) | |
| iter = 2253, accuracy (avg) = 0.870096 (all), 0.879336 (pos), 0.861667 (neg) | |
| data reader: epoch = 0, batch = 2254 / 4040 | |
| iter = 2254, cls_loss (cur) = 0.186048, cls_loss (avg) = 0.304159, lr = 0.010000 | |
| iter = 2254, accuracy (cur) = 0.960000 (all), 1.000000 (pos), 0.923077 (neg) | |
| iter = 2254, accuracy (avg) = 0.870995 (all), 0.880543 (pos), 0.862282 (neg) | |
| data reader: epoch = 0, batch = 2255 / 4040 | |
| iter = 2255, cls_loss (cur) = 0.292618, cls_loss (avg) = 0.304044, lr = 0.010000 | |
| iter = 2255, accuracy (cur) = 0.840000 (all), 0.851852 (pos), 0.826087 (neg) | |
| iter = 2255, accuracy (avg) = 0.870685 (all), 0.880256 (pos), 0.861920 (neg) | |
| data reader: epoch = 0, batch = 2256 / 4040 | |
| iter = 2256, cls_loss (cur) = 0.311797, cls_loss (avg) = 0.304121, lr = 0.010000 | |
| iter = 2256, accuracy (cur) = 0.840000 (all), 0.833333 (pos), 0.846154 (neg) | |
| iter = 2256, accuracy (avg) = 0.870378 (all), 0.879787 (pos), 0.861762 (neg) | |
| data reader: epoch = 0, batch = 2257 / 4040 | |
| iter = 2257, cls_loss (cur) = 0.379422, cls_loss (avg) = 0.304874, lr = 0.010000 | |
| iter = 2257, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 2257, accuracy (avg) = 0.870075 (all), 0.879084 (pos), 0.861765 (neg) | |
| data reader: epoch = 0, batch = 2258 / 4040 | |
| iter = 2258, cls_loss (cur) = 0.253371, cls_loss (avg) = 0.304359, lr = 0.010000 | |
| iter = 2258, accuracy (cur) = 0.940000 (all), 0.916667 (pos), 0.961538 (neg) | |
| iter = 2258, accuracy (avg) = 0.870774 (all), 0.879460 (pos), 0.862763 (neg) | |
| data reader: epoch = 0, batch = 2259 / 4040 | |
| iter = 2259, cls_loss (cur) = 0.242629, cls_loss (avg) = 0.303742, lr = 0.010000 | |
| iter = 2259, accuracy (cur) = 0.880000 (all), 0.866667 (pos), 0.900000 (neg) | |
| iter = 2259, accuracy (avg) = 0.870866 (all), 0.879332 (pos), 0.863135 (neg) | |
| data reader: epoch = 0, batch = 2260 / 4040 | |
| iter = 2260, cls_loss (cur) = 0.265997, cls_loss (avg) = 0.303364, lr = 0.010000 | |
| iter = 2260, accuracy (cur) = 0.900000 (all), 0.960000 (pos), 0.840000 (neg) | |
| iter = 2260, accuracy (avg) = 0.871158 (all), 0.880139 (pos), 0.862904 (neg) | |
| data reader: epoch = 0, batch = 2261 / 4040 | |
| iter = 2261, cls_loss (cur) = 0.301454, cls_loss (avg) = 0.303345, lr = 0.010000 | |
| iter = 2261, accuracy (cur) = 0.880000 (all), 0.857143 (pos), 0.909091 (neg) | |
| iter = 2261, accuracy (avg) = 0.871246 (all), 0.879909 (pos), 0.863366 (neg) | |
| data reader: epoch = 0, batch = 2262 / 4040 | |
| iter = 2262, cls_loss (cur) = 0.267162, cls_loss (avg) = 0.302983, lr = 0.010000 | |
| iter = 2262, accuracy (cur) = 0.900000 (all), 0.869565 (pos), 0.925926 (neg) | |
| iter = 2262, accuracy (avg) = 0.871533 (all), 0.879805 (pos), 0.863991 (neg) | |
| data reader: epoch = 0, batch = 2263 / 4040 | |
| iter = 2263, cls_loss (cur) = 0.258174, cls_loss (avg) = 0.302535, lr = 0.010000 | |
| iter = 2263, accuracy (cur) = 0.920000 (all), 0.880000 (pos), 0.960000 (neg) | |
| iter = 2263, accuracy (avg) = 0.872018 (all), 0.879807 (pos), 0.864951 (neg) | |
| data reader: epoch = 0, batch = 2264 / 4040 | |
| iter = 2264, cls_loss (cur) = 0.225176, cls_loss (avg) = 0.301762, lr = 0.010000 | |
| iter = 2264, accuracy (cur) = 0.920000 (all), 0.884615 (pos), 0.958333 (neg) | |
| iter = 2264, accuracy (avg) = 0.872498 (all), 0.879855 (pos), 0.865885 (neg) | |
| data reader: epoch = 0, batch = 2265 / 4040 | |
| iter = 2265, cls_loss (cur) = 0.342526, cls_loss (avg) = 0.302169, lr = 0.010000 | |
| iter = 2265, accuracy (cur) = 0.820000 (all), 0.806452 (pos), 0.842105 (neg) | |
| iter = 2265, accuracy (avg) = 0.871973 (all), 0.879121 (pos), 0.865647 (neg) | |
| data reader: epoch = 0, batch = 2266 / 4040 | |
| iter = 2266, cls_loss (cur) = 0.247153, cls_loss (avg) = 0.301619, lr = 0.010000 | |
| iter = 2266, accuracy (cur) = 0.880000 (all), 0.846154 (pos), 0.916667 (neg) | |
| iter = 2266, accuracy (avg) = 0.872053 (all), 0.878792 (pos), 0.866158 (neg) | |
| data reader: epoch = 0, batch = 2267 / 4040 | |
| iter = 2267, cls_loss (cur) = 0.243277, cls_loss (avg) = 0.301036, lr = 0.010000 | |
| iter = 2267, accuracy (cur) = 0.920000 (all), 0.967742 (pos), 0.842105 (neg) | |
| iter = 2267, accuracy (avg) = 0.872533 (all), 0.879681 (pos), 0.865917 (neg) | |
| data reader: epoch = 0, batch = 2268 / 4040 | |
| iter = 2268, cls_loss (cur) = 0.275567, cls_loss (avg) = 0.300781, lr = 0.010000 | |
| iter = 2268, accuracy (cur) = 0.860000 (all), 0.826087 (pos), 0.888889 (neg) | |
| iter = 2268, accuracy (avg) = 0.872407 (all), 0.879145 (pos), 0.866147 (neg) | |
| data reader: epoch = 0, batch = 2269 / 4040 | |
| iter = 2269, cls_loss (cur) = 0.333556, cls_loss (avg) = 0.301109, lr = 0.010000 | |
| iter = 2269, accuracy (cur) = 0.860000 (all), 0.960000 (pos), 0.760000 (neg) | |
| iter = 2269, accuracy (avg) = 0.872283 (all), 0.879954 (pos), 0.865085 (neg) | |
| data reader: epoch = 0, batch = 2270 / 4040 | |
| iter = 2270, cls_loss (cur) = 0.511016, cls_loss (avg) = 0.303208, lr = 0.010000 | |
| iter = 2270, accuracy (cur) = 0.740000 (all), 0.950000 (pos), 0.600000 (neg) | |
| iter = 2270, accuracy (avg) = 0.870960 (all), 0.880654 (pos), 0.862434 (neg) | |
| data reader: epoch = 0, batch = 2271 / 4040 | |
| iter = 2271, cls_loss (cur) = 0.464434, cls_loss (avg) = 0.304820, lr = 0.010000 | |
| iter = 2271, accuracy (cur) = 0.760000 (all), 0.740741 (pos), 0.782609 (neg) | |
| iter = 2271, accuracy (avg) = 0.869851 (all), 0.879255 (pos), 0.861636 (neg) | |
| data reader: epoch = 0, batch = 2272 / 4040 | |
| iter = 2272, cls_loss (cur) = 0.346236, cls_loss (avg) = 0.305234, lr = 0.010000 | |
| iter = 2272, accuracy (cur) = 0.800000 (all), 0.884615 (pos), 0.708333 (neg) | |
| iter = 2272, accuracy (avg) = 0.869152 (all), 0.879309 (pos), 0.860103 (neg) | |
| data reader: epoch = 0, batch = 2273 / 4040 | |
| iter = 2273, cls_loss (cur) = 0.182067, cls_loss (avg) = 0.304003, lr = 0.010000 | |
| iter = 2273, accuracy (cur) = 0.920000 (all), 0.880000 (pos), 0.960000 (neg) | |
| iter = 2273, accuracy (avg) = 0.869661 (all), 0.879316 (pos), 0.861102 (neg) | |
| data reader: epoch = 0, batch = 2274 / 4040 | |
| iter = 2274, cls_loss (cur) = 0.177995, cls_loss (avg) = 0.302743, lr = 0.010000 | |
| iter = 2274, accuracy (cur) = 0.940000 (all), 1.000000 (pos), 0.888889 (neg) | |
| iter = 2274, accuracy (avg) = 0.870364 (all), 0.880522 (pos), 0.861380 (neg) | |
| data reader: epoch = 0, batch = 2275 / 4040 | |
| iter = 2275, cls_loss (cur) = 0.277320, cls_loss (avg) = 0.302488, lr = 0.010000 | |
| iter = 2275, accuracy (cur) = 0.840000 (all), 0.857143 (pos), 0.827586 (neg) | |
| iter = 2275, accuracy (avg) = 0.870061 (all), 0.880289 (pos), 0.861042 (neg) | |
| data reader: epoch = 0, batch = 2276 / 4040 | |
| iter = 2276, cls_loss (cur) = 0.267054, cls_loss (avg) = 0.302134, lr = 0.010000 | |
| iter = 2276, accuracy (cur) = 0.940000 (all), 0.875000 (pos), 1.000000 (neg) | |
| iter = 2276, accuracy (avg) = 0.870760 (all), 0.880236 (pos), 0.862432 (neg) | |
| data reader: epoch = 0, batch = 2277 / 4040 | |
| iter = 2277, cls_loss (cur) = 0.394930, cls_loss (avg) = 0.303062, lr = 0.010000 | |
| iter = 2277, accuracy (cur) = 0.860000 (all), 0.833333 (pos), 0.884615 (neg) | |
| iter = 2277, accuracy (avg) = 0.870652 (all), 0.879767 (pos), 0.862653 (neg) | |
| data reader: epoch = 0, batch = 2278 / 4040 | |
| iter = 2278, cls_loss (cur) = 0.358520, cls_loss (avg) = 0.303617, lr = 0.010000 | |
| iter = 2278, accuracy (cur) = 0.800000 (all), 0.818182 (pos), 0.785714 (neg) | |
| iter = 2278, accuracy (avg) = 0.869946 (all), 0.879151 (pos), 0.861884 (neg) | |
| data reader: epoch = 0, batch = 2279 / 4040 | |
| iter = 2279, cls_loss (cur) = 0.196465, cls_loss (avg) = 0.302545, lr = 0.010000 | |
| iter = 2279, accuracy (cur) = 0.940000 (all), 0.916667 (pos), 0.961538 (neg) | |
| iter = 2279, accuracy (avg) = 0.870646 (all), 0.879526 (pos), 0.862881 (neg) | |
| data reader: epoch = 0, batch = 2280 / 4040 | |
| iter = 2280, cls_loss (cur) = 0.344078, cls_loss (avg) = 0.302960, lr = 0.010000 | |
| iter = 2280, accuracy (cur) = 0.820000 (all), 0.791667 (pos), 0.846154 (neg) | |
| iter = 2280, accuracy (avg) = 0.870140 (all), 0.878647 (pos), 0.862713 (neg) | |
| data reader: epoch = 0, batch = 2281 / 4040 | |
| iter = 2281, cls_loss (cur) = 0.356916, cls_loss (avg) = 0.303500, lr = 0.010000 | |
| iter = 2281, accuracy (cur) = 0.860000 (all), 0.838710 (pos), 0.894737 (neg) | |
| iter = 2281, accuracy (avg) = 0.870039 (all), 0.878248 (pos), 0.863034 (neg) | |
| data reader: epoch = 0, batch = 2282 / 4040 | |
| iter = 2282, cls_loss (cur) = 0.331292, cls_loss (avg) = 0.303778, lr = 0.010000 | |
| iter = 2282, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 2282, accuracy (avg) = 0.869938 (all), 0.878354 (pos), 0.862664 (neg) | |
| data reader: epoch = 0, batch = 2283 / 4040 | |
| iter = 2283, cls_loss (cur) = 0.364900, cls_loss (avg) = 0.304389, lr = 0.010000 | |
| iter = 2283, accuracy (cur) = 0.860000 (all), 0.843750 (pos), 0.888889 (neg) | |
| iter = 2283, accuracy (avg) = 0.869839 (all), 0.878008 (pos), 0.862926 (neg) | |
| data reader: epoch = 0, batch = 2284 / 4040 | |
| iter = 2284, cls_loss (cur) = 0.360601, cls_loss (avg) = 0.304951, lr = 0.010000 | |
| iter = 2284, accuracy (cur) = 0.840000 (all), 0.769231 (pos), 0.916667 (neg) | |
| iter = 2284, accuracy (avg) = 0.869540 (all), 0.876921 (pos), 0.863464 (neg) | |
| data reader: epoch = 0, batch = 2285 / 4040 | |
| iter = 2285, cls_loss (cur) = 0.216059, cls_loss (avg) = 0.304062, lr = 0.010000 | |
| iter = 2285, accuracy (cur) = 0.960000 (all), 0.956522 (pos), 0.962963 (neg) | |
| iter = 2285, accuracy (avg) = 0.870445 (all), 0.877717 (pos), 0.864459 (neg) | |
| data reader: epoch = 0, batch = 2286 / 4040 | |
| iter = 2286, cls_loss (cur) = 0.308209, cls_loss (avg) = 0.304104, lr = 0.010000 | |
| iter = 2286, accuracy (cur) = 0.860000 (all), 0.920000 (pos), 0.800000 (neg) | |
| iter = 2286, accuracy (avg) = 0.870341 (all), 0.878140 (pos), 0.863814 (neg) | |
| data reader: epoch = 0, batch = 2287 / 4040 | |
| iter = 2287, cls_loss (cur) = 0.350939, cls_loss (avg) = 0.304572, lr = 0.010000 | |
| iter = 2287, accuracy (cur) = 0.800000 (all), 0.875000 (pos), 0.730769 (neg) | |
| iter = 2287, accuracy (avg) = 0.869637 (all), 0.878108 (pos), 0.862484 (neg) | |
| data reader: epoch = 0, batch = 2288 / 4040 | |
| iter = 2288, cls_loss (cur) = 0.403921, cls_loss (avg) = 0.305566, lr = 0.010000 | |
| iter = 2288, accuracy (cur) = 0.760000 (all), 0.875000 (pos), 0.653846 (neg) | |
| iter = 2288, accuracy (avg) = 0.868541 (all), 0.878077 (pos), 0.860397 (neg) | |
| data reader: epoch = 0, batch = 2289 / 4040 | |
| iter = 2289, cls_loss (cur) = 0.397010, cls_loss (avg) = 0.306480, lr = 0.010000 | |
| iter = 2289, accuracy (cur) = 0.820000 (all), 0.888889 (pos), 0.781250 (neg) | |
| iter = 2289, accuracy (avg) = 0.868055 (all), 0.878185 (pos), 0.859606 (neg) | |
| data reader: epoch = 0, batch = 2290 / 4040 | |
| iter = 2290, cls_loss (cur) = 0.306234, cls_loss (avg) = 0.306478, lr = 0.010000 | |
| iter = 2290, accuracy (cur) = 0.840000 (all), 0.956522 (pos), 0.740741 (neg) | |
| iter = 2290, accuracy (avg) = 0.867775 (all), 0.878969 (pos), 0.858417 (neg) | |
| data reader: epoch = 0, batch = 2291 / 4040 | |
| iter = 2291, cls_loss (cur) = 0.450373, cls_loss (avg) = 0.307917, lr = 0.010000 | |
| iter = 2291, accuracy (cur) = 0.800000 (all), 0.800000 (pos), 0.800000 (neg) | |
| iter = 2291, accuracy (avg) = 0.867097 (all), 0.878179 (pos), 0.857833 (neg) | |
| data reader: epoch = 0, batch = 2292 / 4040 | |
| iter = 2292, cls_loss (cur) = 0.261367, cls_loss (avg) = 0.307451, lr = 0.010000 | |
| iter = 2292, accuracy (cur) = 0.880000 (all), 0.866667 (pos), 0.900000 (neg) | |
| iter = 2292, accuracy (avg) = 0.867226 (all), 0.878064 (pos), 0.858255 (neg) | |
| data reader: epoch = 0, batch = 2293 / 4040 | |
| iter = 2293, cls_loss (cur) = 0.295650, cls_loss (avg) = 0.307333, lr = 0.010000 | |
| iter = 2293, accuracy (cur) = 0.860000 (all), 0.750000 (pos), 1.000000 (neg) | |
| iter = 2293, accuracy (avg) = 0.867154 (all), 0.876783 (pos), 0.859672 (neg) | |
| data reader: epoch = 0, batch = 2294 / 4040 | |
| iter = 2294, cls_loss (cur) = 0.163328, cls_loss (avg) = 0.305893, lr = 0.010000 | |
| iter = 2294, accuracy (cur) = 0.980000 (all), 1.000000 (pos), 0.964286 (neg) | |
| iter = 2294, accuracy (avg) = 0.868282 (all), 0.878015 (pos), 0.860718 (neg) | |
| data reader: epoch = 0, batch = 2295 / 4040 | |
| iter = 2295, cls_loss (cur) = 0.196370, cls_loss (avg) = 0.304798, lr = 0.010000 | |
| iter = 2295, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.862069 (neg) | |
| iter = 2295, accuracy (avg) = 0.868799 (all), 0.879235 (pos), 0.860732 (neg) | |
| data reader: epoch = 0, batch = 2296 / 4040 | |
| iter = 2296, cls_loss (cur) = 0.279055, cls_loss (avg) = 0.304540, lr = 0.010000 | |
| iter = 2296, accuracy (cur) = 0.900000 (all), 0.809524 (pos), 0.965517 (neg) | |
| iter = 2296, accuracy (avg) = 0.869111 (all), 0.878538 (pos), 0.861780 (neg) | |
| data reader: epoch = 0, batch = 2297 / 4040 | |
| iter = 2297, cls_loss (cur) = 0.300080, cls_loss (avg) = 0.304496, lr = 0.010000 | |
| iter = 2297, accuracy (cur) = 0.840000 (all), 0.842105 (pos), 0.838710 (neg) | |
| iter = 2297, accuracy (avg) = 0.868820 (all), 0.878174 (pos), 0.861549 (neg) | |
| data reader: epoch = 0, batch = 2298 / 4040 | |
| iter = 2298, cls_loss (cur) = 0.314208, cls_loss (avg) = 0.304593, lr = 0.010000 | |
| iter = 2298, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 2298, accuracy (avg) = 0.868732 (all), 0.877540 (pos), 0.862064 (neg) | |
| data reader: epoch = 0, batch = 2299 / 4040 | |
| iter = 2299, cls_loss (cur) = 0.306446, cls_loss (avg) = 0.304611, lr = 0.010000 | |
| iter = 2299, accuracy (cur) = 0.820000 (all), 0.826087 (pos), 0.814815 (neg) | |
| iter = 2299, accuracy (avg) = 0.868245 (all), 0.877026 (pos), 0.861591 (neg) | |
| data reader: epoch = 0, batch = 2300 / 4040 | |
| iter = 2300, cls_loss (cur) = 0.278774, cls_loss (avg) = 0.304353, lr = 0.010000 | |
| iter = 2300, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.880000 (neg) | |
| iter = 2300, accuracy (avg) = 0.867962 (all), 0.876255 (pos), 0.861776 (neg) | |
| data reader: epoch = 0, batch = 2301 / 4040 | |
| iter = 2301, cls_loss (cur) = 0.282035, cls_loss (avg) = 0.304130, lr = 0.010000 | |
| iter = 2301, accuracy (cur) = 0.880000 (all), 0.791667 (pos), 0.961538 (neg) | |
| iter = 2301, accuracy (avg) = 0.868083 (all), 0.875409 (pos), 0.862773 (neg) | |
| data reader: epoch = 0, batch = 2302 / 4040 | |
| iter = 2302, cls_loss (cur) = 0.396285, cls_loss (avg) = 0.305051, lr = 0.010000 | |
| iter = 2302, accuracy (cur) = 0.820000 (all), 0.760000 (pos), 0.880000 (neg) | |
| iter = 2302, accuracy (avg) = 0.867602 (all), 0.874255 (pos), 0.862945 (neg) | |
| data reader: epoch = 0, batch = 2303 / 4040 | |
| iter = 2303, cls_loss (cur) = 0.275206, cls_loss (avg) = 0.304753, lr = 0.010000 | |
| iter = 2303, accuracy (cur) = 0.900000 (all), 0.903226 (pos), 0.894737 (neg) | |
| iter = 2303, accuracy (avg) = 0.867926 (all), 0.874545 (pos), 0.863263 (neg) | |
| data reader: epoch = 0, batch = 2304 / 4040 | |
| iter = 2304, cls_loss (cur) = 0.269508, cls_loss (avg) = 0.304400, lr = 0.010000 | |
| iter = 2304, accuracy (cur) = 0.920000 (all), 0.906250 (pos), 0.944444 (neg) | |
| iter = 2304, accuracy (avg) = 0.868447 (all), 0.874862 (pos), 0.864075 (neg) | |
| data reader: epoch = 0, batch = 2305 / 4040 | |
| iter = 2305, cls_loss (cur) = 0.330214, cls_loss (avg) = 0.304659, lr = 0.010000 | |
| iter = 2305, accuracy (cur) = 0.880000 (all), 1.000000 (pos), 0.785714 (neg) | |
| iter = 2305, accuracy (avg) = 0.868562 (all), 0.876113 (pos), 0.863292 (neg) | |
| data reader: epoch = 0, batch = 2306 / 4040 | |
| iter = 2306, cls_loss (cur) = 0.340938, cls_loss (avg) = 0.305021, lr = 0.010000 | |
| iter = 2306, accuracy (cur) = 0.820000 (all), 0.884615 (pos), 0.750000 (neg) | |
| iter = 2306, accuracy (avg) = 0.868077 (all), 0.876198 (pos), 0.862159 (neg) | |
| data reader: epoch = 0, batch = 2307 / 4040 | |
| iter = 2307, cls_loss (cur) = 0.287433, cls_loss (avg) = 0.304846, lr = 0.010000 | |
| iter = 2307, accuracy (cur) = 0.880000 (all), 0.888889 (pos), 0.875000 (neg) | |
| iter = 2307, accuracy (avg) = 0.868196 (all), 0.876325 (pos), 0.862287 (neg) | |
| data reader: epoch = 0, batch = 2308 / 4040 | |
| iter = 2308, cls_loss (cur) = 0.255194, cls_loss (avg) = 0.304349, lr = 0.010000 | |
| iter = 2308, accuracy (cur) = 0.900000 (all), 0.960000 (pos), 0.840000 (neg) | |
| iter = 2308, accuracy (avg) = 0.868514 (all), 0.877162 (pos), 0.862064 (neg) | |
| data reader: epoch = 0, batch = 2309 / 4040 | |
| iter = 2309, cls_loss (cur) = 0.226405, cls_loss (avg) = 0.303570, lr = 0.010000 | |
| iter = 2309, accuracy (cur) = 0.900000 (all), 0.961538 (pos), 0.833333 (neg) | |
| iter = 2309, accuracy (avg) = 0.868829 (all), 0.878006 (pos), 0.861777 (neg) | |
| data reader: epoch = 0, batch = 2310 / 4040 | |
| iter = 2310, cls_loss (cur) = 0.221367, cls_loss (avg) = 0.302748, lr = 0.010000 | |
| iter = 2310, accuracy (cur) = 0.920000 (all), 0.933333 (pos), 0.900000 (neg) | |
| iter = 2310, accuracy (avg) = 0.869340 (all), 0.878559 (pos), 0.862159 (neg) | |
| data reader: epoch = 0, batch = 2311 / 4040 | |
| iter = 2311, cls_loss (cur) = 0.430157, cls_loss (avg) = 0.304022, lr = 0.010000 | |
| iter = 2311, accuracy (cur) = 0.780000 (all), 0.869565 (pos), 0.703704 (neg) | |
| iter = 2311, accuracy (avg) = 0.868447 (all), 0.878469 (pos), 0.860575 (neg) | |
| data reader: epoch = 0, batch = 2312 / 4040 | |
| iter = 2312, cls_loss (cur) = 0.356230, cls_loss (avg) = 0.304544, lr = 0.010000 | |
| iter = 2312, accuracy (cur) = 0.800000 (all), 0.681818 (pos), 0.892857 (neg) | |
| iter = 2312, accuracy (avg) = 0.867763 (all), 0.876503 (pos), 0.860897 (neg) | |
| data reader: epoch = 0, batch = 2313 / 4040 | |
| iter = 2313, cls_loss (cur) = 0.222532, cls_loss (avg) = 0.303724, lr = 0.010000 | |
| iter = 2313, accuracy (cur) = 0.940000 (all), 0.863636 (pos), 1.000000 (neg) | |
| iter = 2313, accuracy (avg) = 0.868485 (all), 0.876374 (pos), 0.862288 (neg) | |
| data reader: epoch = 0, batch = 2314 / 4040 | |
| iter = 2314, cls_loss (cur) = 0.218691, cls_loss (avg) = 0.302873, lr = 0.010000 | |
| iter = 2314, accuracy (cur) = 0.940000 (all), 0.900000 (pos), 0.966667 (neg) | |
| iter = 2314, accuracy (avg) = 0.869200 (all), 0.876610 (pos), 0.863332 (neg) | |
| data reader: epoch = 0, batch = 2315 / 4040 | |
| iter = 2315, cls_loss (cur) = 0.296745, cls_loss (avg) = 0.302812, lr = 0.010000 | |
| iter = 2315, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 2315, accuracy (avg) = 0.868908 (all), 0.875939 (pos), 0.863320 (neg) | |
| data reader: epoch = 0, batch = 2316 / 4040 | |
| iter = 2316, cls_loss (cur) = 0.364064, cls_loss (avg) = 0.303424, lr = 0.010000 | |
| iter = 2316, accuracy (cur) = 0.860000 (all), 0.760000 (pos), 0.960000 (neg) | |
| iter = 2316, accuracy (avg) = 0.868819 (all), 0.874780 (pos), 0.864286 (neg) | |
| data reader: epoch = 0, batch = 2317 / 4040 | |
| iter = 2317, cls_loss (cur) = 0.212730, cls_loss (avg) = 0.302518, lr = 0.010000 | |
| iter = 2317, accuracy (cur) = 0.940000 (all), 0.909091 (pos), 0.964286 (neg) | |
| iter = 2317, accuracy (avg) = 0.869531 (all), 0.875123 (pos), 0.865286 (neg) | |
| data reader: epoch = 0, batch = 2318 / 4040 | |
| iter = 2318, cls_loss (cur) = 0.411602, cls_loss (avg) = 0.303608, lr = 0.010000 | |
| iter = 2318, accuracy (cur) = 0.760000 (all), 0.777778 (pos), 0.739130 (neg) | |
| iter = 2318, accuracy (avg) = 0.868435 (all), 0.874150 (pos), 0.864025 (neg) | |
| data reader: epoch = 0, batch = 2319 / 4040 | |
| iter = 2319, cls_loss (cur) = 0.321254, cls_loss (avg) = 0.303785, lr = 0.010000 | |
| iter = 2319, accuracy (cur) = 0.880000 (all), 0.821429 (pos), 0.954545 (neg) | |
| iter = 2319, accuracy (avg) = 0.868551 (all), 0.873622 (pos), 0.864930 (neg) | |
| data reader: epoch = 0, batch = 2320 / 4040 | |
| iter = 2320, cls_loss (cur) = 0.331258, cls_loss (avg) = 0.304060, lr = 0.010000 | |
| iter = 2320, accuracy (cur) = 0.820000 (all), 0.636364 (pos), 0.964286 (neg) | |
| iter = 2320, accuracy (avg) = 0.868066 (all), 0.871250 (pos), 0.865924 (neg) | |
| data reader: epoch = 0, batch = 2321 / 4040 | |
| iter = 2321, cls_loss (cur) = 0.416676, cls_loss (avg) = 0.305186, lr = 0.010000 | |
| iter = 2321, accuracy (cur) = 0.740000 (all), 0.766667 (pos), 0.700000 (neg) | |
| iter = 2321, accuracy (avg) = 0.866785 (all), 0.870204 (pos), 0.864264 (neg) | |
| data reader: epoch = 0, batch = 2322 / 4040 | |
| iter = 2322, cls_loss (cur) = 0.383869, cls_loss (avg) = 0.305973, lr = 0.010000 | |
| iter = 2322, accuracy (cur) = 0.800000 (all), 0.827586 (pos), 0.761905 (neg) | |
| iter = 2322, accuracy (avg) = 0.866117 (all), 0.869778 (pos), 0.863241 (neg) | |
| data reader: epoch = 0, batch = 2323 / 4040 | |
| iter = 2323, cls_loss (cur) = 0.235651, cls_loss (avg) = 0.305269, lr = 0.010000 | |
| iter = 2323, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.851852 (neg) | |
| iter = 2323, accuracy (avg) = 0.866656 (all), 0.871080 (pos), 0.863127 (neg) | |
| data reader: epoch = 0, batch = 2324 / 4040 | |
| iter = 2324, cls_loss (cur) = 0.228895, cls_loss (avg) = 0.304506, lr = 0.010000 | |
| iter = 2324, accuracy (cur) = 0.920000 (all), 1.000000 (pos), 0.833333 (neg) | |
| iter = 2324, accuracy (avg) = 0.867189 (all), 0.872369 (pos), 0.862829 (neg) | |
| data reader: epoch = 0, batch = 2325 / 4040 | |
| iter = 2325, cls_loss (cur) = 0.255141, cls_loss (avg) = 0.304012, lr = 0.010000 | |
| iter = 2325, accuracy (cur) = 0.860000 (all), 0.888889 (pos), 0.826087 (neg) | |
| iter = 2325, accuracy (avg) = 0.867117 (all), 0.872534 (pos), 0.862461 (neg) | |
| data reader: epoch = 0, batch = 2326 / 4040 | |
| iter = 2326, cls_loss (cur) = 0.182894, cls_loss (avg) = 0.302801, lr = 0.010000 | |
| iter = 2326, accuracy (cur) = 0.940000 (all), 0.965517 (pos), 0.904762 (neg) | |
| iter = 2326, accuracy (avg) = 0.867846 (all), 0.873464 (pos), 0.862884 (neg) | |
| data reader: epoch = 0, batch = 2327 / 4040 | |
| iter = 2327, cls_loss (cur) = 0.426108, cls_loss (avg) = 0.304034, lr = 0.010000 | |
| iter = 2327, accuracy (cur) = 0.780000 (all), 0.800000 (pos), 0.771429 (neg) | |
| iter = 2327, accuracy (avg) = 0.866968 (all), 0.872730 (pos), 0.861970 (neg) | |
| data reader: epoch = 0, batch = 2328 / 4040 | |
| iter = 2328, cls_loss (cur) = 0.265875, cls_loss (avg) = 0.303652, lr = 0.010000 | |
| iter = 2328, accuracy (cur) = 0.880000 (all), 0.833333 (pos), 0.923077 (neg) | |
| iter = 2328, accuracy (avg) = 0.867098 (all), 0.872336 (pos), 0.862581 (neg) | |
| data reader: epoch = 0, batch = 2329 / 4040 | |
| iter = 2329, cls_loss (cur) = 0.271449, cls_loss (avg) = 0.303330, lr = 0.010000 | |
| iter = 2329, accuracy (cur) = 0.900000 (all), 0.870968 (pos), 0.947368 (neg) | |
| iter = 2329, accuracy (avg) = 0.867427 (all), 0.872322 (pos), 0.863429 (neg) | |
| data reader: epoch = 0, batch = 2330 / 4040 | |
| iter = 2330, cls_loss (cur) = 0.296358, cls_loss (avg) = 0.303261, lr = 0.010000 | |
| iter = 2330, accuracy (cur) = 0.860000 (all), 0.916667 (pos), 0.807692 (neg) | |
| iter = 2330, accuracy (avg) = 0.867353 (all), 0.872765 (pos), 0.862871 (neg) | |
| data reader: epoch = 0, batch = 2331 / 4040 | |
| iter = 2331, cls_loss (cur) = 0.385919, cls_loss (avg) = 0.304087, lr = 0.010000 | |
| iter = 2331, accuracy (cur) = 0.800000 (all), 0.900000 (pos), 0.733333 (neg) | |
| iter = 2331, accuracy (avg) = 0.866679 (all), 0.873038 (pos), 0.861576 (neg) | |
| data reader: epoch = 0, batch = 2332 / 4040 | |
| iter = 2332, cls_loss (cur) = 0.321475, cls_loss (avg) = 0.304261, lr = 0.010000 | |
| iter = 2332, accuracy (cur) = 0.860000 (all), 0.814815 (pos), 0.913043 (neg) | |
| iter = 2332, accuracy (avg) = 0.866613 (all), 0.872456 (pos), 0.862091 (neg) | |
| data reader: epoch = 0, batch = 2333 / 4040 | |
| iter = 2333, cls_loss (cur) = 0.312187, cls_loss (avg) = 0.304340, lr = 0.010000 | |
| iter = 2333, accuracy (cur) = 0.880000 (all), 0.962963 (pos), 0.782609 (neg) | |
| iter = 2333, accuracy (avg) = 0.866746 (all), 0.873361 (pos), 0.861296 (neg) | |
| data reader: epoch = 0, batch = 2334 / 4040 | |
| iter = 2334, cls_loss (cur) = 0.260954, cls_loss (avg) = 0.303906, lr = 0.010000 | |
| iter = 2334, accuracy (cur) = 0.900000 (all), 0.869565 (pos), 0.925926 (neg) | |
| iter = 2334, accuracy (avg) = 0.867079 (all), 0.873323 (pos), 0.861942 (neg) | |
| data reader: epoch = 0, batch = 2335 / 4040 | |
| iter = 2335, cls_loss (cur) = 0.322016, cls_loss (avg) = 0.304087, lr = 0.010000 | |
| iter = 2335, accuracy (cur) = 0.840000 (all), 0.772727 (pos), 0.892857 (neg) | |
| iter = 2335, accuracy (avg) = 0.866808 (all), 0.872317 (pos), 0.862251 (neg) | |
| data reader: epoch = 0, batch = 2336 / 4040 | |
| iter = 2336, cls_loss (cur) = 0.467974, cls_loss (avg) = 0.305726, lr = 0.010000 | |
| iter = 2336, accuracy (cur) = 0.780000 (all), 0.760000 (pos), 0.800000 (neg) | |
| iter = 2336, accuracy (avg) = 0.865940 (all), 0.871194 (pos), 0.861629 (neg) | |
| data reader: epoch = 0, batch = 2337 / 4040 | |
| iter = 2337, cls_loss (cur) = 0.167785, cls_loss (avg) = 0.304347, lr = 0.010000 | |
| iter = 2337, accuracy (cur) = 0.960000 (all), 0.909091 (pos), 1.000000 (neg) | |
| iter = 2337, accuracy (avg) = 0.866881 (all), 0.871573 (pos), 0.863013 (neg) | |
| data reader: epoch = 0, batch = 2338 / 4040 | |
| iter = 2338, cls_loss (cur) = 0.325061, cls_loss (avg) = 0.304554, lr = 0.010000 | |
| iter = 2338, accuracy (cur) = 0.840000 (all), 0.800000 (pos), 0.866667 (neg) | |
| iter = 2338, accuracy (avg) = 0.866612 (all), 0.870857 (pos), 0.863049 (neg) | |
| data reader: epoch = 0, batch = 2339 / 4040 | |
| iter = 2339, cls_loss (cur) = 0.354569, cls_loss (avg) = 0.305054, lr = 0.010000 | |
| iter = 2339, accuracy (cur) = 0.840000 (all), 0.809524 (pos), 0.862069 (neg) | |
| iter = 2339, accuracy (avg) = 0.866346 (all), 0.870244 (pos), 0.863039 (neg) | |
| data reader: epoch = 0, batch = 2340 / 4040 | |
| iter = 2340, cls_loss (cur) = 0.425997, cls_loss (avg) = 0.306264, lr = 0.010000 | |
| iter = 2340, accuracy (cur) = 0.780000 (all), 0.642857 (pos), 0.954545 (neg) | |
| iter = 2340, accuracy (avg) = 0.865482 (all), 0.867970 (pos), 0.863954 (neg) | |
| data reader: epoch = 0, batch = 2341 / 4040 | |
| iter = 2341, cls_loss (cur) = 0.273056, cls_loss (avg) = 0.305932, lr = 0.010000 | |
| iter = 2341, accuracy (cur) = 0.880000 (all), 0.826087 (pos), 0.925926 (neg) | |
| iter = 2341, accuracy (avg) = 0.865628 (all), 0.867551 (pos), 0.864574 (neg) | |
| data reader: epoch = 0, batch = 2342 / 4040 | |
| iter = 2342, cls_loss (cur) = 0.423643, cls_loss (avg) = 0.307109, lr = 0.010000 | |
| iter = 2342, accuracy (cur) = 0.760000 (all), 0.681818 (pos), 0.821429 (neg) | |
| iter = 2342, accuracy (avg) = 0.864571 (all), 0.865693 (pos), 0.864143 (neg) | |
| data reader: epoch = 0, batch = 2343 / 4040 | |
| iter = 2343, cls_loss (cur) = 0.247026, cls_loss (avg) = 0.306508, lr = 0.010000 | |
| iter = 2343, accuracy (cur) = 0.880000 (all), 0.866667 (pos), 0.900000 (neg) | |
| iter = 2343, accuracy (avg) = 0.864726 (all), 0.865703 (pos), 0.864501 (neg) | |
| data reader: epoch = 0, batch = 2344 / 4040 | |
| iter = 2344, cls_loss (cur) = 0.284873, cls_loss (avg) = 0.306291, lr = 0.010000 | |
| iter = 2344, accuracy (cur) = 0.880000 (all), 0.954545 (pos), 0.821429 (neg) | |
| iter = 2344, accuracy (avg) = 0.864878 (all), 0.866592 (pos), 0.864071 (neg) | |
| data reader: epoch = 0, batch = 2345 / 4040 | |
| iter = 2345, cls_loss (cur) = 0.210942, cls_loss (avg) = 0.305338, |
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