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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- super_glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: 1_7e-3_5_0.1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# 1_7e-3_5_0.1 |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the super_glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9635 |
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- Accuracy: 0.7382 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.007 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 11 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 100.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.4151 | 1.0 | 590 | 1.1624 | 0.6217 | |
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| 1.4557 | 2.0 | 1180 | 0.9521 | 0.4489 | |
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| 1.2723 | 3.0 | 1770 | 3.3480 | 0.3795 | |
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| 1.1923 | 4.0 | 2360 | 1.0321 | 0.4761 | |
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| 1.2283 | 5.0 | 2950 | 1.7063 | 0.6217 | |
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| 1.0486 | 6.0 | 3540 | 0.8079 | 0.6566 | |
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| 0.983 | 7.0 | 4130 | 2.7141 | 0.4119 | |
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| 1.061 | 8.0 | 4720 | 1.2305 | 0.6407 | |
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| 0.9617 | 9.0 | 5310 | 0.9103 | 0.6654 | |
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| 0.9218 | 10.0 | 5900 | 1.0764 | 0.5728 | |
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| 0.8804 | 11.0 | 6490 | 0.7290 | 0.7034 | |
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| 0.8314 | 12.0 | 7080 | 0.7770 | 0.7080 | |
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| 0.7805 | 13.0 | 7670 | 0.7321 | 0.7165 | |
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| 0.7474 | 14.0 | 8260 | 0.7924 | 0.6667 | |
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| 0.7693 | 15.0 | 8850 | 0.8842 | 0.7150 | |
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| 0.7532 | 16.0 | 9440 | 0.6981 | 0.7174 | |
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| 0.6803 | 17.0 | 10030 | 1.2782 | 0.6064 | |
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| 0.6888 | 18.0 | 10620 | 0.9639 | 0.7061 | |
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| 0.6432 | 19.0 | 11210 | 0.8320 | 0.7174 | |
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| 0.6091 | 20.0 | 11800 | 0.8192 | 0.7144 | |
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| 0.5904 | 21.0 | 12390 | 1.0849 | 0.7089 | |
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| 0.5754 | 22.0 | 12980 | 0.8291 | 0.6823 | |
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| 0.539 | 23.0 | 13570 | 1.1292 | 0.7128 | |
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| 0.525 | 24.0 | 14160 | 0.8724 | 0.6942 | |
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| 0.5346 | 25.0 | 14750 | 0.8999 | 0.7067 | |
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| 0.5164 | 26.0 | 15340 | 1.5764 | 0.5832 | |
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| 0.4874 | 27.0 | 15930 | 1.1817 | 0.6581 | |
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| 0.439 | 28.0 | 16520 | 1.0572 | 0.6719 | |
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| 0.4388 | 29.0 | 17110 | 0.9059 | 0.7376 | |
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| 0.4096 | 30.0 | 17700 | 0.8708 | 0.7028 | |
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| 0.4117 | 31.0 | 18290 | 0.9059 | 0.7379 | |
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| 0.401 | 32.0 | 18880 | 0.8226 | 0.7303 | |
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| 0.3763 | 33.0 | 19470 | 0.8717 | 0.7248 | |
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| 0.3629 | 34.0 | 20060 | 0.9393 | 0.7046 | |
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| 0.33 | 35.0 | 20650 | 0.8766 | 0.7248 | |
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| 0.3598 | 36.0 | 21240 | 1.0561 | 0.7315 | |
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| 0.3211 | 37.0 | 21830 | 0.9181 | 0.7021 | |
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| 0.3146 | 38.0 | 22420 | 0.8177 | 0.7303 | |
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| 0.322 | 39.0 | 23010 | 0.9637 | 0.7336 | |
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| 0.2963 | 40.0 | 23600 | 1.0769 | 0.7128 | |
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| 0.3265 | 41.0 | 24190 | 1.0980 | 0.7330 | |
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| 0.276 | 42.0 | 24780 | 0.8939 | 0.7422 | |
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| 0.2953 | 43.0 | 25370 | 1.0178 | 0.7303 | |
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| 0.2669 | 44.0 | 25960 | 1.0061 | 0.7150 | |
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| 0.2613 | 45.0 | 26550 | 1.0087 | 0.7076 | |
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| 0.257 | 46.0 | 27140 | 0.8887 | 0.7122 | |
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| 0.2586 | 47.0 | 27730 | 1.0173 | 0.7327 | |
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| 0.2492 | 48.0 | 28320 | 1.0005 | 0.7324 | |
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| 0.2572 | 49.0 | 28910 | 0.9586 | 0.7226 | |
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| 0.2388 | 50.0 | 29500 | 0.9336 | 0.7318 | |
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| 0.218 | 51.0 | 30090 | 1.0072 | 0.7220 | |
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| 0.2353 | 52.0 | 30680 | 0.8747 | 0.7343 | |
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| 0.2252 | 53.0 | 31270 | 0.9927 | 0.7361 | |
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| 0.2239 | 54.0 | 31860 | 0.9873 | 0.7281 | |
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| 0.2289 | 55.0 | 32450 | 1.0668 | 0.7098 | |
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| 0.2108 | 56.0 | 33040 | 0.8821 | 0.7306 | |
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| 0.197 | 57.0 | 33630 | 0.9667 | 0.7287 | |
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| 0.2045 | 58.0 | 34220 | 0.8937 | 0.7294 | |
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| 0.2092 | 59.0 | 34810 | 1.1175 | 0.7110 | |
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| 0.2115 | 60.0 | 35400 | 1.0294 | 0.7330 | |
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| 0.2051 | 61.0 | 35990 | 0.9363 | 0.7349 | |
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| 0.1947 | 62.0 | 36580 | 0.9427 | 0.7278 | |
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| 0.1918 | 63.0 | 37170 | 1.0344 | 0.7226 | |
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| 0.1911 | 64.0 | 37760 | 0.9883 | 0.7324 | |
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| 0.1875 | 65.0 | 38350 | 0.9878 | 0.7281 | |
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| 0.181 | 66.0 | 38940 | 1.0037 | 0.7306 | |
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| 0.1844 | 67.0 | 39530 | 1.0300 | 0.7309 | |
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| 0.172 | 68.0 | 40120 | 0.9785 | 0.7275 | |
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| 0.1728 | 69.0 | 40710 | 1.0590 | 0.7413 | |
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| 0.1756 | 70.0 | 41300 | 0.9992 | 0.7248 | |
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| 0.1671 | 71.0 | 41890 | 1.0583 | 0.7061 | |
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| 0.1824 | 72.0 | 42480 | 1.0114 | 0.7361 | |
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| 0.1638 | 73.0 | 43070 | 0.9866 | 0.7266 | |
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| 0.159 | 74.0 | 43660 | 1.0436 | 0.7242 | |
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| 0.168 | 75.0 | 44250 | 1.0963 | 0.7364 | |
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| 0.1637 | 76.0 | 44840 | 0.9260 | 0.7300 | |
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| 0.1583 | 77.0 | 45430 | 0.9472 | 0.7309 | |
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| 0.161 | 78.0 | 46020 | 0.9540 | 0.7300 | |
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| 0.1485 | 79.0 | 46610 | 0.9537 | 0.7294 | |
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| 0.1566 | 80.0 | 47200 | 1.0064 | 0.7248 | |
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| 0.1499 | 81.0 | 47790 | 0.9961 | 0.7358 | |
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| 0.1529 | 82.0 | 48380 | 0.9872 | 0.7410 | |
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| 0.1545 | 83.0 | 48970 | 1.0003 | 0.7309 | |
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| 0.1481 | 84.0 | 49560 | 0.9471 | 0.7349 | |
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| 0.1492 | 85.0 | 50150 | 0.9946 | 0.7235 | |
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| 0.1402 | 86.0 | 50740 | 1.0070 | 0.7394 | |
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| 0.1437 | 87.0 | 51330 | 0.9976 | 0.7379 | |
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| 0.1368 | 88.0 | 51920 | 0.9900 | 0.7355 | |
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| 0.1394 | 89.0 | 52510 | 1.0081 | 0.7333 | |
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| 0.1376 | 90.0 | 53100 | 0.9910 | 0.7349 | |
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| 0.1402 | 91.0 | 53690 | 0.9569 | 0.7358 | |
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| 0.1397 | 92.0 | 54280 | 0.9660 | 0.7346 | |
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| 0.1311 | 93.0 | 54870 | 0.9787 | 0.7291 | |
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| 0.1389 | 94.0 | 55460 | 0.9653 | 0.7343 | |
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| 0.1315 | 95.0 | 56050 | 0.9494 | 0.7346 | |
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| 0.1301 | 96.0 | 56640 | 0.9705 | 0.7333 | |
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| 0.133 | 97.0 | 57230 | 0.9615 | 0.7355 | |
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| 0.1293 | 98.0 | 57820 | 0.9686 | 0.7312 | |
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| 0.1332 | 99.0 | 58410 | 0.9759 | 0.7346 | |
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| 0.1306 | 100.0 | 59000 | 0.9635 | 0.7382 | |
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### Framework versions |
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- Transformers 4.30.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
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