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sembr2023-bert-tiny

Token Classification
Transformers
PyTorch
bert
Generated from Trainer
Inference Endpoints
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  1. README.md +110 -134
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -3,8 +3,6 @@ license: mit
3
  base_model: prajjwal1/bert-tiny
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  tags:
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  - generated_from_trainer
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- datasets:
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- - sembr2023
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  metrics:
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  - precision
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  - recall
@@ -12,29 +10,7 @@ metrics:
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  - accuracy
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  model-index:
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  - name: sembr2023-bert-tiny
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- results:
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- - task:
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- name: Token Classification
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- type: token-classification
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- dataset:
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- name: sembr2023
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- type: sembr2023
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- config: sembr2023
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- split: test
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- args: sembr2023
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- metrics:
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- - name: Precision
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- type: precision
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- value: 0.7287362872204017
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- - name: Recall
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- type: recall
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- value: 0.6756042794875181
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- - name: F1
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- type: f1
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- value: 0.7011651816312543
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- - name: Accuracy
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- type: accuracy
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- value: 0.9490469679439985
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  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,16 +18,16 @@ should probably proofread and complete it, then remove this comment. -->
42
 
43
  # sembr2023-bert-tiny
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45
- This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on the sembr2023 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2172
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- - Precision: 0.7287
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- - Recall: 0.6756
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- - F1: 0.7012
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- - Iou: 0.5398
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- - Accuracy: 0.9490
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- - Balanced Accuracy: 0.8256
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- - Overall Accuracy: 0.9348
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  ## Model description
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@@ -82,106 +58,106 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Iou | Accuracy | Balanced Accuracy | Overall Accuracy |
84
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:--------:|:-----------------:|:----------------:|
85
- | 1.422 | 0.07 | 10 | 1.3253 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9114 | 0.4999 | 0.9114 |
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- | 0.8436 | 0.14 | 20 | 0.7947 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
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- | 0.6272 | 0.21 | 30 | 0.5924 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
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- | 0.4967 | 0.28 | 40 | 0.5178 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
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- | 0.4864 | 0.35 | 50 | 0.4818 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
90
- | 0.4554 | 0.42 | 60 | 0.4575 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
91
- | 0.4635 | 0.49 | 70 | 0.4410 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
92
- | 0.4238 | 0.56 | 80 | 0.4261 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
93
- | 0.4104 | 0.62 | 90 | 0.4136 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
94
- | 0.3832 | 0.69 | 100 | 0.3958 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
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- | 0.3664 | 0.76 | 110 | 0.3693 | 0 | 0.0 | 0.0 | 0.0 | 0.9115 | 0.5 | 0.9115 |
96
- | 0.3736 | 0.83 | 120 | 0.3477 | 0.5263 | 0.0013 | 0.0026 | 0.0013 | 0.9115 | 0.5006 | 0.9115 |
97
- | 0.3364 | 0.9 | 130 | 0.3317 | 0.5220 | 0.0110 | 0.0215 | 0.0109 | 0.9116 | 0.5050 | 0.9115 |
98
- | 0.3095 | 0.97 | 140 | 0.3221 | 0.5584 | 0.0556 | 0.1011 | 0.0533 | 0.9126 | 0.5257 | 0.9118 |
99
- | 0.3233 | 1.04 | 150 | 0.3156 | 0.5713 | 0.1471 | 0.2340 | 0.1325 | 0.9148 | 0.5682 | 0.9129 |
100
- | 0.3072 | 1.11 | 160 | 0.3112 | 0.6452 | 0.1640 | 0.2616 | 0.1505 | 0.9181 | 0.5776 | 0.9160 |
101
- | 0.287 | 1.18 | 170 | 0.3075 | 0.6336 | 0.2622 | 0.3709 | 0.2277 | 0.9213 | 0.6237 | 0.9177 |
102
- | 0.3061 | 1.25 | 180 | 0.3039 | 0.7025 | 0.2142 | 0.3283 | 0.1964 | 0.9224 | 0.6027 | 0.9189 |
103
- | 0.2924 | 1.32 | 190 | 0.2997 | 0.7581 | 0.1511 | 0.2520 | 0.1442 | 0.9206 | 0.5732 | 0.9183 |
104
- | 0.3081 | 1.39 | 200 | 0.2950 | 0.7367 | 0.2025 | 0.3177 | 0.1888 | 0.9230 | 0.5977 | 0.9193 |
105
- | 0.2993 | 1.46 | 210 | 0.2921 | 0.6861 | 0.2902 | 0.4079 | 0.2562 | 0.9255 | 0.6387 | 0.9200 |
106
- | 0.275 | 1.53 | 220 | 0.2885 | 0.6734 | 0.3249 | 0.4383 | 0.2807 | 0.9263 | 0.6548 | 0.9200 |
107
- | 0.2692 | 1.6 | 230 | 0.2861 | 0.6622 | 0.3438 | 0.4526 | 0.2925 | 0.9264 | 0.6634 | 0.9188 |
108
- | 0.2536 | 1.67 | 240 | 0.2828 | 0.6295 | 0.3895 | 0.4812 | 0.3169 | 0.9257 | 0.6836 | 0.9176 |
109
- | 0.265 | 1.74 | 250 | 0.2790 | 0.6586 | 0.3546 | 0.4610 | 0.2996 | 0.9266 | 0.6684 | 0.9200 |
110
- | 0.2571 | 1.81 | 260 | 0.2736 | 0.6641 | 0.3729 | 0.4776 | 0.3137 | 0.9278 | 0.6773 | 0.9208 |
111
- | 0.2684 | 1.88 | 270 | 0.2711 | 0.6794 | 0.4142 | 0.5146 | 0.3465 | 0.9309 | 0.6976 | 0.9222 |
112
- | 0.2754 | 1.94 | 280 | 0.2721 | 0.6408 | 0.4813 | 0.5497 | 0.3790 | 0.9302 | 0.7276 | 0.9198 |
113
- | 0.2507 | 2.01 | 290 | 0.2652 | 0.6922 | 0.4438 | 0.5408 | 0.3707 | 0.9333 | 0.7123 | 0.9240 |
114
- | 0.2678 | 2.08 | 300 | 0.2622 | 0.6957 | 0.4243 | 0.5271 | 0.3578 | 0.9326 | 0.7031 | 0.9244 |
115
- | 0.2676 | 2.15 | 310 | 0.2629 | 0.6698 | 0.5020 | 0.5739 | 0.4024 | 0.9340 | 0.7390 | 0.9228 |
116
- | 0.2369 | 2.22 | 320 | 0.2596 | 0.6667 | 0.5123 | 0.5794 | 0.4079 | 0.9342 | 0.7437 | 0.9233 |
117
- | 0.2293 | 2.29 | 330 | 0.2560 | 0.6741 | 0.5174 | 0.5854 | 0.4138 | 0.9352 | 0.7465 | 0.9240 |
118
- | 0.235 | 2.36 | 340 | 0.2517 | 0.7160 | 0.4796 | 0.5744 | 0.4030 | 0.9371 | 0.7306 | 0.9270 |
119
- | 0.209 | 2.43 | 350 | 0.2545 | 0.6704 | 0.5332 | 0.5940 | 0.4225 | 0.9355 | 0.7539 | 0.9236 |
120
- | 0.2032 | 2.5 | 360 | 0.2486 | 0.7002 | 0.5130 | 0.5922 | 0.4206 | 0.9375 | 0.7458 | 0.9267 |
121
- | 0.2005 | 2.57 | 370 | 0.2482 | 0.6870 | 0.5418 | 0.6058 | 0.4345 | 0.9376 | 0.7589 | 0.9259 |
122
- | 0.206 | 2.64 | 380 | 0.2463 | 0.6949 | 0.5384 | 0.6067 | 0.4354 | 0.9382 | 0.7577 | 0.9264 |
123
- | 0.2196 | 2.71 | 390 | 0.2421 | 0.7158 | 0.5237 | 0.6049 | 0.4336 | 0.9395 | 0.7518 | 0.9289 |
124
- | 0.1863 | 2.78 | 400 | 0.2410 | 0.7072 | 0.5435 | 0.6146 | 0.4437 | 0.9397 | 0.7608 | 0.9282 |
125
- | 0.2036 | 2.85 | 410 | 0.2408 | 0.6889 | 0.5775 | 0.6283 | 0.4580 | 0.9395 | 0.7761 | 0.9272 |
126
- | 0.1982 | 2.92 | 420 | 0.2345 | 0.7198 | 0.5596 | 0.6297 | 0.4595 | 0.9418 | 0.7692 | 0.9300 |
127
- | 0.1909 | 2.99 | 430 | 0.2327 | 0.7173 | 0.5830 | 0.6432 | 0.4741 | 0.9428 | 0.7804 | 0.9307 |
128
- | 0.2286 | 3.06 | 440 | 0.2309 | 0.7250 | 0.5933 | 0.6526 | 0.4843 | 0.9441 | 0.7857 | 0.9317 |
129
- | 0.1839 | 3.12 | 450 | 0.2305 | 0.7219 | 0.6159 | 0.6647 | 0.4978 | 0.9450 | 0.7964 | 0.9323 |
130
- | 0.2086 | 3.19 | 460 | 0.2280 | 0.7252 | 0.6171 | 0.6668 | 0.5002 | 0.9454 | 0.7972 | 0.9328 |
131
- | 0.2055 | 3.26 | 470 | 0.2302 | 0.7088 | 0.6450 | 0.6754 | 0.5099 | 0.9451 | 0.8096 | 0.9318 |
132
- | 0.1925 | 3.33 | 480 | 0.2252 | 0.7309 | 0.6263 | 0.6746 | 0.5090 | 0.9465 | 0.8020 | 0.9336 |
133
- | 0.165 | 3.4 | 490 | 0.2248 | 0.7254 | 0.6364 | 0.6780 | 0.5128 | 0.9465 | 0.8065 | 0.9336 |
134
- | 0.1814 | 3.47 | 500 | 0.2283 | 0.7008 | 0.6637 | 0.6818 | 0.5172 | 0.9452 | 0.8181 | 0.9314 |
135
- | 0.1812 | 3.54 | 510 | 0.2239 | 0.7275 | 0.6436 | 0.6830 | 0.5186 | 0.9471 | 0.8101 | 0.9336 |
136
- | 0.1738 | 3.61 | 520 | 0.2237 | 0.7241 | 0.6498 | 0.6850 | 0.5209 | 0.9471 | 0.8129 | 0.9335 |
137
- | 0.1726 | 3.68 | 530 | 0.2227 | 0.7271 | 0.6517 | 0.6873 | 0.5236 | 0.9475 | 0.8140 | 0.9338 |
138
- | 0.188 | 3.75 | 540 | 0.2204 | 0.7407 | 0.6393 | 0.6863 | 0.5224 | 0.9483 | 0.8088 | 0.9348 |
139
- | 0.187 | 3.82 | 550 | 0.2185 | 0.7539 | 0.6303 | 0.6866 | 0.5227 | 0.9491 | 0.8052 | 0.9362 |
140
- | 0.1917 | 3.89 | 560 | 0.2193 | 0.7354 | 0.6532 | 0.6919 | 0.5289 | 0.9485 | 0.8152 | 0.9349 |
141
- | 0.1794 | 3.96 | 570 | 0.2197 | 0.7326 | 0.6574 | 0.6929 | 0.5301 | 0.9485 | 0.8170 | 0.9346 |
142
- | 0.1541 | 4.03 | 580 | 0.2203 | 0.7292 | 0.6645 | 0.6954 | 0.5330 | 0.9485 | 0.8203 | 0.9343 |
143
- | 0.1837 | 4.1 | 590 | 0.2190 | 0.7336 | 0.6563 | 0.6928 | 0.5300 | 0.9485 | 0.8166 | 0.9349 |
144
- | 0.1541 | 4.17 | 600 | 0.2177 | 0.7405 | 0.6467 | 0.6904 | 0.5272 | 0.9487 | 0.8123 | 0.9354 |
145
- | 0.1721 | 4.24 | 610 | 0.2210 | 0.7178 | 0.6767 | 0.6966 | 0.5345 | 0.9479 | 0.8254 | 0.9338 |
146
- | 0.1657 | 4.31 | 620 | 0.2186 | 0.7323 | 0.6628 | 0.6958 | 0.5335 | 0.9487 | 0.8196 | 0.9350 |
147
- | 0.1792 | 4.38 | 630 | 0.2182 | 0.7294 | 0.6668 | 0.6967 | 0.5345 | 0.9486 | 0.8214 | 0.9349 |
148
- | 0.1908 | 4.44 | 640 | 0.2183 | 0.7309 | 0.6648 | 0.6963 | 0.5341 | 0.9487 | 0.8205 | 0.9348 |
149
- | 0.1581 | 4.51 | 650 | 0.2177 | 0.7330 | 0.6658 | 0.6978 | 0.5359 | 0.9490 | 0.8211 | 0.9349 |
150
- | 0.169 | 4.58 | 660 | 0.2178 | 0.7313 | 0.6685 | 0.6985 | 0.5366 | 0.9489 | 0.8223 | 0.9347 |
151
- | 0.1756 | 4.65 | 670 | 0.2184 | 0.7271 | 0.6723 | 0.6986 | 0.5369 | 0.9487 | 0.8239 | 0.9344 |
152
- | 0.1563 | 4.72 | 680 | 0.2179 | 0.7311 | 0.6706 | 0.6996 | 0.5379 | 0.9490 | 0.8233 | 0.9349 |
153
- | 0.1684 | 4.79 | 690 | 0.2161 | 0.7475 | 0.6565 | 0.6990 | 0.5373 | 0.9500 | 0.8175 | 0.9362 |
154
- | 0.1585 | 4.86 | 700 | 0.2171 | 0.7380 | 0.6648 | 0.6995 | 0.5378 | 0.9495 | 0.8209 | 0.9354 |
155
- | 0.1841 | 4.93 | 710 | 0.2181 | 0.7283 | 0.6745 | 0.7004 | 0.5389 | 0.9489 | 0.8251 | 0.9346 |
156
- | 0.1724 | 5.0 | 720 | 0.2177 | 0.7323 | 0.6695 | 0.6995 | 0.5379 | 0.9491 | 0.8229 | 0.9349 |
157
- | 0.1791 | 5.07 | 730 | 0.2170 | 0.7329 | 0.6708 | 0.7005 | 0.5391 | 0.9492 | 0.8236 | 0.9351 |
158
- | 0.1712 | 5.14 | 740 | 0.2171 | 0.7344 | 0.6705 | 0.7010 | 0.5396 | 0.9494 | 0.8235 | 0.9354 |
159
- | 0.1489 | 5.21 | 750 | 0.2164 | 0.7374 | 0.6683 | 0.7012 | 0.5398 | 0.9496 | 0.8226 | 0.9357 |
160
- | 0.157 | 5.28 | 760 | 0.2161 | 0.7407 | 0.6636 | 0.7000 | 0.5385 | 0.9497 | 0.8205 | 0.9358 |
161
- | 0.1686 | 5.35 | 770 | 0.2180 | 0.7262 | 0.6775 | 0.7010 | 0.5396 | 0.9489 | 0.8263 | 0.9345 |
162
- | 0.1526 | 5.42 | 780 | 0.2168 | 0.7344 | 0.6690 | 0.7002 | 0.5387 | 0.9493 | 0.8228 | 0.9351 |
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- | 0.1542 | 5.49 | 790 | 0.2172 | 0.7313 | 0.6722 | 0.7005 | 0.5390 | 0.9491 | 0.8241 | 0.9349 |
164
- | 0.1498 | 5.56 | 800 | 0.2168 | 0.7351 | 0.6691 | 0.7005 | 0.5391 | 0.9494 | 0.8229 | 0.9353 |
165
- | 0.1571 | 5.62 | 810 | 0.2167 | 0.7348 | 0.6687 | 0.7002 | 0.5387 | 0.9493 | 0.8227 | 0.9354 |
166
- | 0.1682 | 5.69 | 820 | 0.2175 | 0.7265 | 0.6775 | 0.7011 | 0.5398 | 0.9489 | 0.8263 | 0.9347 |
167
- | 0.1688 | 5.76 | 830 | 0.2175 | 0.7267 | 0.6764 | 0.7006 | 0.5392 | 0.9489 | 0.8259 | 0.9347 |
168
- | 0.1622 | 5.83 | 840 | 0.2161 | 0.7393 | 0.6633 | 0.6992 | 0.5376 | 0.9495 | 0.8203 | 0.9357 |
169
- | 0.1547 | 5.9 | 850 | 0.2173 | 0.7282 | 0.6755 | 0.7008 | 0.5395 | 0.9490 | 0.8255 | 0.9347 |
170
- | 0.1712 | 5.97 | 860 | 0.2166 | 0.7339 | 0.6701 | 0.7005 | 0.5391 | 0.9493 | 0.8232 | 0.9352 |
171
- | 0.1632 | 6.04 | 870 | 0.2168 | 0.7317 | 0.6724 | 0.7008 | 0.5394 | 0.9492 | 0.8242 | 0.9352 |
172
- | 0.1615 | 6.11 | 880 | 0.2167 | 0.7315 | 0.6727 | 0.7009 | 0.5395 | 0.9492 | 0.8244 | 0.9352 |
173
- | 0.1543 | 6.18 | 890 | 0.2164 | 0.7348 | 0.6699 | 0.7008 | 0.5395 | 0.9494 | 0.8232 | 0.9354 |
174
- | 0.1407 | 6.25 | 900 | 0.2168 | 0.7318 | 0.6726 | 0.7009 | 0.5396 | 0.9492 | 0.8243 | 0.9351 |
175
- | 0.1607 | 6.32 | 910 | 0.2170 | 0.7299 | 0.6743 | 0.7010 | 0.5396 | 0.9491 | 0.8250 | 0.9350 |
176
- | 0.1652 | 6.39 | 920 | 0.2172 | 0.7276 | 0.6760 | 0.7009 | 0.5395 | 0.9489 | 0.8257 | 0.9347 |
177
- | 0.1676 | 6.46 | 930 | 0.2173 | 0.7274 | 0.6765 | 0.7010 | 0.5397 | 0.9489 | 0.8260 | 0.9347 |
178
- | 0.14 | 6.53 | 940 | 0.2174 | 0.7267 | 0.6767 | 0.7008 | 0.5394 | 0.9489 | 0.8260 | 0.9346 |
179
- | 0.1634 | 6.6 | 950 | 0.2173 | 0.7276 | 0.6764 | 0.7011 | 0.5397 | 0.9490 | 0.8259 | 0.9347 |
180
- | 0.174 | 6.67 | 960 | 0.2172 | 0.7283 | 0.6759 | 0.7011 | 0.5398 | 0.9490 | 0.8257 | 0.9348 |
181
- | 0.156 | 6.74 | 970 | 0.2172 | 0.7287 | 0.6759 | 0.7013 | 0.5400 | 0.9491 | 0.8257 | 0.9348 |
182
- | 0.1641 | 6.81 | 980 | 0.2172 | 0.7287 | 0.6756 | 0.7012 | 0.5398 | 0.9490 | 0.8256 | 0.9348 |
183
- | 0.1634 | 6.88 | 990 | 0.2172 | 0.7287 | 0.6756 | 0.7012 | 0.5398 | 0.9490 | 0.8256 | 0.9348 |
184
- | 0.1753 | 6.94 | 1000 | 0.2172 | 0.7287 | 0.6756 | 0.7012 | 0.5398 | 0.9490 | 0.8256 | 0.9348 |
185
 
186
 
187
  ### Framework versions
 
3
  base_model: prajjwal1/bert-tiny
4
  tags:
5
  - generated_from_trainer
 
 
6
  metrics:
7
  - precision
8
  - recall
 
10
  - accuracy
11
  model-index:
12
  - name: sembr2023-bert-tiny
13
+ results: []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
14
  ---
15
 
16
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
18
 
19
  # sembr2023-bert-tiny
20
 
21
+ This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.2101
24
+ - Precision: 0.7983
25
+ - Recall: 0.6561
26
+ - F1: 0.7202
27
+ - Iou: 0.5628
28
+ - Accuracy: 0.9531
29
+ - Balanced Accuracy: 0.8196
30
+ - Overall Accuracy: 0.9387
31
 
32
  ## Model description
33
 
 
58
 
59
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Iou | Accuracy | Balanced Accuracy | Overall Accuracy |
60
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:--------:|:-----------------:|:----------------:|
61
+ | 1.2554 | 0.06 | 10 | 1.1550 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
62
+ | 0.8047 | 0.12 | 20 | 0.7616 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
63
+ | 0.6392 | 0.18 | 30 | 0.6116 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
64
+ | 0.5328 | 0.24 | 40 | 0.5384 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
65
+ | 0.4859 | 0.3 | 50 | 0.4982 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
66
+ | 0.469 | 0.36 | 60 | 0.4726 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
67
+ | 0.4711 | 0.42 | 70 | 0.4513 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
68
+ | 0.4341 | 0.48 | 80 | 0.4349 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
69
+ | 0.4234 | 0.55 | 90 | 0.4181 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
70
+ | 0.3661 | 0.61 | 100 | 0.3970 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
71
+ | 0.3901 | 0.67 | 110 | 0.3685 | 0 | 0.0 | 0.0 | 0.0 | 0.9080 | 0.5 | 0.9080 |
72
+ | 0.3493 | 0.73 | 120 | 0.3447 | 0.6074 | 0.0126 | 0.0247 | 0.0125 | 0.9084 | 0.5059 | 0.9081 |
73
+ | 0.3199 | 0.79 | 130 | 0.3309 | 0.6329 | 0.0676 | 0.1222 | 0.0651 | 0.9106 | 0.5318 | 0.9095 |
74
+ | 0.3444 | 0.85 | 140 | 0.3219 | 0.6748 | 0.1406 | 0.2328 | 0.1317 | 0.9147 | 0.5669 | 0.9130 |
75
+ | 0.3131 | 0.91 | 150 | 0.3158 | 0.6768 | 0.2211 | 0.3334 | 0.2000 | 0.9187 | 0.6052 | 0.9154 |
76
+ | 0.2921 | 0.97 | 160 | 0.3100 | 0.7245 | 0.1708 | 0.2765 | 0.1604 | 0.9178 | 0.5821 | 0.9156 |
77
+ | 0.3121 | 1.03 | 170 | 0.3057 | 0.6425 | 0.3246 | 0.4313 | 0.2749 | 0.9213 | 0.6531 | 0.9157 |
78
+ | 0.3267 | 1.09 | 180 | 0.3035 | 0.6597 | 0.3155 | 0.4269 | 0.2714 | 0.9221 | 0.6495 | 0.9168 |
79
+ | 0.28 | 1.15 | 190 | 0.2986 | 0.6836 | 0.3429 | 0.4567 | 0.2960 | 0.9250 | 0.6634 | 0.9171 |
80
+ | 0.2945 | 1.21 | 200 | 0.2929 | 0.7005 | 0.3078 | 0.4276 | 0.2720 | 0.9242 | 0.6472 | 0.9177 |
81
+ | 0.2744 | 1.27 | 210 | 0.2874 | 0.7108 | 0.3406 | 0.4606 | 0.2992 | 0.9266 | 0.6633 | 0.9183 |
82
+ | 0.2563 | 1.33 | 220 | 0.2866 | 0.6712 | 0.4432 | 0.5339 | 0.3641 | 0.9288 | 0.7106 | 0.9182 |
83
+ | 0.2565 | 1.39 | 230 | 0.2793 | 0.7057 | 0.4187 | 0.5256 | 0.3565 | 0.9305 | 0.7005 | 0.9203 |
84
+ | 0.2383 | 1.45 | 240 | 0.2760 | 0.6918 | 0.4493 | 0.5448 | 0.3744 | 0.9309 | 0.7145 | 0.9197 |
85
+ | 0.2477 | 1.52 | 250 | 0.2698 | 0.7317 | 0.4190 | 0.5328 | 0.3632 | 0.9324 | 0.7017 | 0.9218 |
86
+ | 0.2466 | 1.58 | 260 | 0.2674 | 0.7119 | 0.4605 | 0.5593 | 0.3882 | 0.9332 | 0.7208 | 0.9212 |
87
+ | 0.2623 | 1.64 | 270 | 0.2641 | 0.7071 | 0.4675 | 0.5629 | 0.3917 | 0.9332 | 0.7240 | 0.9220 |
88
+ | 0.2308 | 1.7 | 280 | 0.2622 | 0.7169 | 0.4797 | 0.5748 | 0.4033 | 0.9347 | 0.7303 | 0.9225 |
89
+ | 0.2179 | 1.76 | 290 | 0.2577 | 0.7287 | 0.4678 | 0.5698 | 0.3984 | 0.9350 | 0.7251 | 0.9236 |
90
+ | 0.2347 | 1.82 | 300 | 0.2557 | 0.7425 | 0.4651 | 0.5719 | 0.4005 | 0.9360 | 0.7244 | 0.9246 |
91
+ | 0.2175 | 1.88 | 310 | 0.2549 | 0.7314 | 0.4873 | 0.5849 | 0.4133 | 0.9364 | 0.7346 | 0.9244 |
92
+ | 0.2365 | 1.94 | 320 | 0.2524 | 0.7237 | 0.5057 | 0.5954 | 0.4239 | 0.9368 | 0.7431 | 0.9244 |
93
+ | 0.2068 | 2.0 | 330 | 0.2513 | 0.7569 | 0.4744 | 0.5832 | 0.4117 | 0.9376 | 0.7295 | 0.9260 |
94
+ | 0.2004 | 2.06 | 340 | 0.2506 | 0.6962 | 0.5462 | 0.6122 | 0.4411 | 0.9363 | 0.7611 | 0.9234 |
95
+ | 0.231 | 2.12 | 350 | 0.2490 | 0.7145 | 0.5251 | 0.6053 | 0.4340 | 0.9370 | 0.7519 | 0.9241 |
96
+ | 0.2117 | 2.18 | 360 | 0.2457 | 0.7300 | 0.5132 | 0.6027 | 0.4314 | 0.9378 | 0.7470 | 0.9257 |
97
+ | 0.1768 | 2.24 | 370 | 0.2450 | 0.7281 | 0.5273 | 0.6116 | 0.4405 | 0.9384 | 0.7537 | 0.9256 |
98
+ | 0.2013 | 2.3 | 380 | 0.2433 | 0.7198 | 0.5513 | 0.6244 | 0.4539 | 0.9390 | 0.7648 | 0.9258 |
99
+ | 0.2128 | 2.36 | 390 | 0.2405 | 0.7568 | 0.5214 | 0.6174 | 0.4466 | 0.9406 | 0.7522 | 0.9282 |
100
+ | 0.2186 | 2.42 | 400 | 0.2393 | 0.7560 | 0.5215 | 0.6173 | 0.4464 | 0.9405 | 0.7522 | 0.9279 |
101
+ | 0.2105 | 2.48 | 410 | 0.2408 | 0.6966 | 0.5834 | 0.6350 | 0.4652 | 0.9383 | 0.7788 | 0.9246 |
102
+ | 0.2216 | 2.55 | 420 | 0.2382 | 0.7415 | 0.5493 | 0.6311 | 0.4610 | 0.9409 | 0.7650 | 0.9277 |
103
+ | 0.1816 | 2.61 | 430 | 0.2377 | 0.7258 | 0.5768 | 0.6428 | 0.4736 | 0.9410 | 0.7774 | 0.9274 |
104
+ | 0.2136 | 2.67 | 440 | 0.2352 | 0.7506 | 0.5456 | 0.6319 | 0.4619 | 0.9415 | 0.7636 | 0.9284 |
105
+ | 0.2043 | 2.73 | 450 | 0.2341 | 0.7425 | 0.5615 | 0.6394 | 0.4700 | 0.9418 | 0.7709 | 0.9286 |
106
+ | 0.2014 | 2.79 | 460 | 0.2333 | 0.7565 | 0.5572 | 0.6417 | 0.4725 | 0.9428 | 0.7695 | 0.9297 |
107
+ | 0.1862 | 2.85 | 470 | 0.2306 | 0.7744 | 0.5520 | 0.6446 | 0.4755 | 0.9440 | 0.7678 | 0.9313 |
108
+ | 0.1714 | 2.91 | 480 | 0.2312 | 0.7354 | 0.6083 | 0.6658 | 0.4991 | 0.9438 | 0.7931 | 0.9302 |
109
+ | 0.1693 | 2.97 | 490 | 0.2280 | 0.7637 | 0.5768 | 0.6572 | 0.4895 | 0.9447 | 0.7794 | 0.9314 |
110
+ | 0.2043 | 3.03 | 500 | 0.2288 | 0.7577 | 0.5848 | 0.6601 | 0.4927 | 0.9446 | 0.7830 | 0.9314 |
111
+ | 0.2138 | 3.09 | 510 | 0.2256 | 0.7797 | 0.5650 | 0.6552 | 0.4872 | 0.9453 | 0.7744 | 0.9327 |
112
+ | 0.1914 | 3.15 | 520 | 0.2250 | 0.7732 | 0.5873 | 0.6675 | 0.5010 | 0.9462 | 0.7849 | 0.9330 |
113
+ | 0.1647 | 3.21 | 530 | 0.2240 | 0.7586 | 0.6173 | 0.6807 | 0.5160 | 0.9467 | 0.7987 | 0.9329 |
114
+ | 0.1749 | 3.27 | 540 | 0.2237 | 0.7679 | 0.6108 | 0.6804 | 0.5156 | 0.9472 | 0.7961 | 0.9331 |
115
+ | 0.1883 | 3.33 | 550 | 0.2226 | 0.7839 | 0.5992 | 0.6792 | 0.5143 | 0.9479 | 0.7913 | 0.9344 |
116
+ | 0.1657 | 3.39 | 560 | 0.2196 | 0.7856 | 0.6059 | 0.6841 | 0.5199 | 0.9485 | 0.7946 | 0.9353 |
117
+ | 0.1721 | 3.45 | 570 | 0.2217 | 0.7556 | 0.6408 | 0.6935 | 0.5308 | 0.9479 | 0.8099 | 0.9335 |
118
+ | 0.1843 | 3.52 | 580 | 0.2188 | 0.7935 | 0.6010 | 0.6840 | 0.5197 | 0.9489 | 0.7926 | 0.9354 |
119
+ | 0.1709 | 3.58 | 590 | 0.2175 | 0.7993 | 0.6078 | 0.6905 | 0.5273 | 0.9499 | 0.7962 | 0.9364 |
120
+ | 0.1526 | 3.64 | 600 | 0.2168 | 0.7782 | 0.6380 | 0.7012 | 0.5398 | 0.9500 | 0.8098 | 0.9358 |
121
+ | 0.1614 | 3.7 | 610 | 0.2148 | 0.8129 | 0.6083 | 0.6959 | 0.5336 | 0.9511 | 0.7971 | 0.9380 |
122
+ | 0.1585 | 3.76 | 620 | 0.2149 | 0.8046 | 0.6210 | 0.7010 | 0.5396 | 0.9513 | 0.8029 | 0.9377 |
123
+ | 0.1798 | 3.82 | 630 | 0.2163 | 0.7788 | 0.6476 | 0.7072 | 0.5470 | 0.9507 | 0.8145 | 0.9364 |
124
+ | 0.1637 | 3.88 | 640 | 0.2147 | 0.8000 | 0.6276 | 0.7034 | 0.5425 | 0.9513 | 0.8059 | 0.9375 |
125
+ | 0.1542 | 3.94 | 650 | 0.2138 | 0.8004 | 0.6335 | 0.7072 | 0.5471 | 0.9518 | 0.8088 | 0.9379 |
126
+ | 0.1575 | 4.0 | 660 | 0.2146 | 0.7867 | 0.6464 | 0.7097 | 0.5500 | 0.9514 | 0.8143 | 0.9371 |
127
+ | 0.1632 | 4.06 | 670 | 0.2124 | 0.7998 | 0.6368 | 0.7091 | 0.5493 | 0.9519 | 0.8103 | 0.9380 |
128
+ | 0.1687 | 4.12 | 680 | 0.2112 | 0.8129 | 0.6294 | 0.7095 | 0.5498 | 0.9526 | 0.8074 | 0.9390 |
129
+ | 0.1565 | 4.18 | 690 | 0.2129 | 0.7959 | 0.6429 | 0.7113 | 0.5519 | 0.9520 | 0.8131 | 0.9380 |
130
+ | 0.1869 | 4.24 | 700 | 0.2128 | 0.7896 | 0.6526 | 0.7146 | 0.5559 | 0.9521 | 0.8175 | 0.9378 |
131
+ | 0.1689 | 4.3 | 710 | 0.2119 | 0.8052 | 0.6361 | 0.7107 | 0.5512 | 0.9524 | 0.8102 | 0.9385 |
132
+ | 0.1581 | 4.36 | 720 | 0.2126 | 0.7817 | 0.6618 | 0.7167 | 0.5585 | 0.9519 | 0.8215 | 0.9373 |
133
+ | 0.1683 | 4.42 | 730 | 0.2121 | 0.8019 | 0.6442 | 0.7145 | 0.5558 | 0.9526 | 0.8140 | 0.9384 |
134
+ | 0.1735 | 4.48 | 740 | 0.2111 | 0.8009 | 0.6452 | 0.7147 | 0.5560 | 0.9526 | 0.8145 | 0.9387 |
135
+ | 0.1537 | 4.55 | 750 | 0.2104 | 0.7991 | 0.6461 | 0.7145 | 0.5558 | 0.9525 | 0.8148 | 0.9386 |
136
+ | 0.174 | 4.61 | 760 | 0.2112 | 0.8031 | 0.6454 | 0.7156 | 0.5572 | 0.9528 | 0.8147 | 0.9387 |
137
+ | 0.1662 | 4.67 | 770 | 0.2118 | 0.7897 | 0.6586 | 0.7182 | 0.5603 | 0.9525 | 0.8204 | 0.9378 |
138
+ | 0.1486 | 4.73 | 780 | 0.2113 | 0.8009 | 0.6492 | 0.7171 | 0.5590 | 0.9529 | 0.8164 | 0.9386 |
139
+ | 0.1672 | 4.79 | 790 | 0.2110 | 0.8055 | 0.6461 | 0.7170 | 0.5589 | 0.9531 | 0.8152 | 0.9389 |
140
+ | 0.1553 | 4.85 | 800 | 0.2108 | 0.7969 | 0.6527 | 0.7176 | 0.5596 | 0.9528 | 0.8179 | 0.9383 |
141
+ | 0.1504 | 4.91 | 810 | 0.2106 | 0.8047 | 0.6461 | 0.7167 | 0.5585 | 0.9530 | 0.8151 | 0.9389 |
142
+ | 0.176 | 4.97 | 820 | 0.2103 | 0.8059 | 0.6459 | 0.7171 | 0.5589 | 0.9531 | 0.8151 | 0.9389 |
143
+ | 0.1597 | 5.03 | 830 | 0.2102 | 0.7979 | 0.6535 | 0.7185 | 0.5607 | 0.9529 | 0.8184 | 0.9386 |
144
+ | 0.1437 | 5.09 | 840 | 0.2105 | 0.7977 | 0.6539 | 0.7187 | 0.5609 | 0.9529 | 0.8185 | 0.9385 |
145
+ | 0.1751 | 5.15 | 850 | 0.2104 | 0.8004 | 0.6508 | 0.7179 | 0.5600 | 0.9530 | 0.8172 | 0.9386 |
146
+ | 0.1737 | 5.21 | 860 | 0.2105 | 0.7951 | 0.6573 | 0.7197 | 0.5621 | 0.9529 | 0.8201 | 0.9385 |
147
+ | 0.1683 | 5.27 | 870 | 0.2104 | 0.7953 | 0.6573 | 0.7198 | 0.5622 | 0.9529 | 0.8201 | 0.9385 |
148
+ | 0.1477 | 5.33 | 880 | 0.2102 | 0.7974 | 0.6536 | 0.7184 | 0.5605 | 0.9529 | 0.8184 | 0.9386 |
149
+ | 0.1702 | 5.39 | 890 | 0.2102 | 0.7978 | 0.6532 | 0.7183 | 0.5604 | 0.9529 | 0.8182 | 0.9386 |
150
+ | 0.1478 | 5.45 | 900 | 0.2101 | 0.7985 | 0.6536 | 0.7188 | 0.5611 | 0.9530 | 0.8185 | 0.9386 |
151
+ | 0.1656 | 5.52 | 910 | 0.2099 | 0.8 | 0.6522 | 0.7186 | 0.5608 | 0.9530 | 0.8179 | 0.9387 |
152
+ | 0.1757 | 5.58 | 920 | 0.2099 | 0.7996 | 0.6525 | 0.7186 | 0.5608 | 0.9530 | 0.8180 | 0.9387 |
153
+ | 0.1723 | 5.64 | 930 | 0.2100 | 0.7990 | 0.6536 | 0.7190 | 0.5613 | 0.9530 | 0.8185 | 0.9387 |
154
+ | 0.1472 | 5.7 | 940 | 0.2101 | 0.7976 | 0.6561 | 0.7199 | 0.5624 | 0.9531 | 0.8196 | 0.9386 |
155
+ | 0.1628 | 5.76 | 950 | 0.2102 | 0.7974 | 0.6564 | 0.7201 | 0.5626 | 0.9531 | 0.8198 | 0.9386 |
156
+ | 0.1563 | 5.82 | 960 | 0.2102 | 0.7973 | 0.6564 | 0.7200 | 0.5626 | 0.9531 | 0.8198 | 0.9386 |
157
+ | 0.1893 | 5.88 | 970 | 0.2102 | 0.7979 | 0.6563 | 0.7202 | 0.5628 | 0.9531 | 0.8197 | 0.9387 |
158
+ | 0.1554 | 5.94 | 980 | 0.2101 | 0.7982 | 0.6562 | 0.7203 | 0.5628 | 0.9531 | 0.8197 | 0.9387 |
159
+ | 0.1636 | 6.0 | 990 | 0.2101 | 0.7983 | 0.6561 | 0.7202 | 0.5628 | 0.9531 | 0.8196 | 0.9387 |
160
+ | 0.1588 | 6.06 | 1000 | 0.2101 | 0.7983 | 0.6561 | 0.7202 | 0.5628 | 0.9531 | 0.8196 | 0.9387 |
161
 
162
 
163
  ### Framework versions
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