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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_5e-3_10_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_5e-3_10_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: 0.9323 |
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- Accuracy: 0.7440 |
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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: 0.005 |
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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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| 1.4938 | 1.0 | 590 | 2.3680 | 0.6217 | |
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| 1.4628 | 2.0 | 1180 | 1.4346 | 0.6217 | |
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| 1.3133 | 3.0 | 1770 | 0.9694 | 0.6260 | |
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| 1.268 | 4.0 | 2360 | 1.1126 | 0.6217 | |
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| 1.0913 | 5.0 | 2950 | 0.9254 | 0.6587 | |
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| 1.0518 | 6.0 | 3540 | 0.8635 | 0.6593 | |
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| 1.0309 | 7.0 | 4130 | 1.3201 | 0.5049 | |
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| 0.9539 | 8.0 | 4720 | 0.8164 | 0.6801 | |
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| 0.9364 | 9.0 | 5310 | 1.3605 | 0.6254 | |
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| 0.9419 | 10.0 | 5900 | 0.7974 | 0.6844 | |
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| 0.9314 | 11.0 | 6490 | 1.3755 | 0.5486 | |
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| 0.8216 | 12.0 | 7080 | 0.7721 | 0.7012 | |
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| 0.8582 | 13.0 | 7670 | 0.7902 | 0.6902 | |
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| 0.7695 | 14.0 | 8260 | 0.7552 | 0.6945 | |
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| 0.7901 | 15.0 | 8850 | 0.8217 | 0.7144 | |
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| 0.7382 | 16.0 | 9440 | 0.8028 | 0.6844 | |
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| 0.7009 | 17.0 | 10030 | 0.7778 | 0.6994 | |
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| 0.6922 | 18.0 | 10620 | 0.9600 | 0.6688 | |
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| 0.6409 | 19.0 | 11210 | 0.8214 | 0.7104 | |
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| 0.6419 | 20.0 | 11800 | 1.1320 | 0.7031 | |
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| 0.6205 | 21.0 | 12390 | 0.7671 | 0.7232 | |
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| 0.6242 | 22.0 | 12980 | 0.8438 | 0.7208 | |
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| 0.5749 | 23.0 | 13570 | 1.0312 | 0.7214 | |
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| 0.5669 | 24.0 | 14160 | 0.7602 | 0.7242 | |
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| 0.5499 | 25.0 | 14750 | 0.8538 | 0.7294 | |
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| 0.5258 | 26.0 | 15340 | 1.5849 | 0.5807 | |
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| 0.5256 | 27.0 | 15930 | 0.8285 | 0.7306 | |
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| 0.491 | 28.0 | 16520 | 0.8039 | 0.7180 | |
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| 0.4844 | 29.0 | 17110 | 0.7899 | 0.7382 | |
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| 0.4584 | 30.0 | 17700 | 0.8144 | 0.7309 | |
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| 0.4602 | 31.0 | 18290 | 1.0077 | 0.7196 | |
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| 0.4467 | 32.0 | 18880 | 0.9234 | 0.7306 | |
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| 0.4267 | 33.0 | 19470 | 0.8644 | 0.7174 | |
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| 0.4031 | 34.0 | 20060 | 0.8536 | 0.7226 | |
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| 0.3862 | 35.0 | 20650 | 0.8552 | 0.7385 | |
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| 0.3811 | 36.0 | 21240 | 0.9266 | 0.7373 | |
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| 0.3814 | 37.0 | 21830 | 0.9688 | 0.7147 | |
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| 0.3613 | 38.0 | 22420 | 0.8678 | 0.7434 | |
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| 0.3528 | 39.0 | 23010 | 0.8885 | 0.7309 | |
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| 0.3563 | 40.0 | 23600 | 0.9239 | 0.7446 | |
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| 0.3507 | 41.0 | 24190 | 0.9006 | 0.7450 | |
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| 0.3437 | 42.0 | 24780 | 1.0086 | 0.7281 | |
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| 0.3138 | 43.0 | 25370 | 0.9287 | 0.7361 | |
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| 0.3208 | 44.0 | 25960 | 0.9420 | 0.7318 | |
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| 0.3214 | 45.0 | 26550 | 0.9205 | 0.7339 | |
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| 0.3013 | 46.0 | 27140 | 0.9259 | 0.7248 | |
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| 0.3066 | 47.0 | 27730 | 0.8718 | 0.7388 | |
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| 0.2987 | 48.0 | 28320 | 0.9665 | 0.7214 | |
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| 0.3116 | 49.0 | 28910 | 0.9426 | 0.7410 | |
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| 0.2766 | 50.0 | 29500 | 0.8971 | 0.7428 | |
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| 0.2683 | 51.0 | 30090 | 1.0176 | 0.7437 | |
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| 0.27 | 52.0 | 30680 | 0.9311 | 0.7382 | |
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| 0.2653 | 53.0 | 31270 | 0.9399 | 0.7336 | |
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| 0.2583 | 54.0 | 31860 | 0.8990 | 0.7281 | |
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| 0.2582 | 55.0 | 32450 | 0.9761 | 0.7419 | |
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| 0.2616 | 56.0 | 33040 | 0.8687 | 0.7480 | |
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| 0.2401 | 57.0 | 33630 | 0.9587 | 0.7266 | |
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| 0.2426 | 58.0 | 34220 | 0.9359 | 0.7474 | |
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| 0.2466 | 59.0 | 34810 | 0.9008 | 0.7385 | |
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| 0.2351 | 60.0 | 35400 | 0.9119 | 0.7462 | |
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| 0.237 | 61.0 | 35990 | 0.9495 | 0.7425 | |
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| 0.2329 | 62.0 | 36580 | 0.9731 | 0.7446 | |
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| 0.2235 | 63.0 | 37170 | 0.9495 | 0.7379 | |
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| 0.2251 | 64.0 | 37760 | 0.9236 | 0.7343 | |
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| 0.2235 | 65.0 | 38350 | 0.9289 | 0.7483 | |
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| 0.2237 | 66.0 | 38940 | 0.9300 | 0.7364 | |
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| 0.2159 | 67.0 | 39530 | 0.9430 | 0.7434 | |
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| 0.2201 | 68.0 | 40120 | 0.9144 | 0.7453 | |
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| 0.2075 | 69.0 | 40710 | 0.9126 | 0.7477 | |
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| 0.2195 | 70.0 | 41300 | 0.9387 | 0.7529 | |
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| 0.2036 | 71.0 | 41890 | 0.9798 | 0.7349 | |
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| 0.2116 | 72.0 | 42480 | 1.0175 | 0.7492 | |
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| 0.1953 | 73.0 | 43070 | 0.9082 | 0.7498 | |
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| 0.2003 | 74.0 | 43660 | 0.9919 | 0.7443 | |
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| 0.2016 | 75.0 | 44250 | 0.9649 | 0.7453 | |
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| 0.1997 | 76.0 | 44840 | 0.9454 | 0.7398 | |
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| 0.2065 | 77.0 | 45430 | 0.9424 | 0.7440 | |
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| 0.1983 | 78.0 | 46020 | 0.9516 | 0.7361 | |
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| 0.1937 | 79.0 | 46610 | 0.9370 | 0.7404 | |
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| 0.1826 | 80.0 | 47200 | 0.9395 | 0.7468 | |
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| 0.1816 | 81.0 | 47790 | 0.9566 | 0.7446 | |
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| 0.1931 | 82.0 | 48380 | 0.9800 | 0.7508 | |
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| 0.1866 | 83.0 | 48970 | 0.9390 | 0.7459 | |
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| 0.1831 | 84.0 | 49560 | 0.9383 | 0.7440 | |
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| 0.183 | 85.0 | 50150 | 0.9607 | 0.7422 | |
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| 0.1825 | 86.0 | 50740 | 0.9608 | 0.7468 | |
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| 0.178 | 87.0 | 51330 | 0.9820 | 0.7456 | |
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| 0.1787 | 88.0 | 51920 | 0.9598 | 0.7468 | |
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| 0.1745 | 89.0 | 52510 | 0.9419 | 0.7483 | |
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| 0.1739 | 90.0 | 53100 | 0.9796 | 0.7495 | |
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| 0.1752 | 91.0 | 53690 | 0.9373 | 0.7477 | |
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| 0.1773 | 92.0 | 54280 | 0.9310 | 0.7370 | |
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| 0.1699 | 93.0 | 54870 | 0.9641 | 0.7456 | |
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| 0.1738 | 94.0 | 55460 | 0.9418 | 0.7468 | |
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| 0.1698 | 95.0 | 56050 | 0.9586 | 0.7450 | |
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| 0.1658 | 96.0 | 56640 | 0.9488 | 0.7468 | |
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| 0.1658 | 97.0 | 57230 | 0.9450 | 0.7471 | |
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| 0.1641 | 98.0 | 57820 | 0.9307 | 0.7459 | |
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| 0.1695 | 99.0 | 58410 | 0.9487 | 0.7443 | |
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| 0.1653 | 100.0 | 59000 | 0.9323 | 0.7440 | |
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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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