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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_5_0.9 |
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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_5_0.9 |
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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: 1.0161 |
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- Accuracy: 0.7254 |
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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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| 3.6534 | 1.0 | 590 | 2.9136 | 0.6217 | |
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| 3.1534 | 2.0 | 1180 | 2.7899 | 0.5896 | |
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| 3.1737 | 3.0 | 1770 | 4.1075 | 0.4003 | |
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| 3.108 | 4.0 | 2360 | 2.7570 | 0.6263 | |
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| 2.796 | 5.0 | 2950 | 2.8853 | 0.6122 | |
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| 2.6961 | 6.0 | 3540 | 2.6092 | 0.6083 | |
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| 2.7012 | 7.0 | 4130 | 5.4272 | 0.3899 | |
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| 2.5904 | 8.0 | 4720 | 2.6163 | 0.6110 | |
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| 2.6187 | 9.0 | 5310 | 2.4947 | 0.6440 | |
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| 2.4748 | 10.0 | 5900 | 3.1599 | 0.6343 | |
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| 2.4977 | 11.0 | 6490 | 2.4600 | 0.6358 | |
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| 2.4255 | 12.0 | 7080 | 2.3595 | 0.6165 | |
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| 2.371 | 13.0 | 7670 | 2.2762 | 0.6505 | |
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| 2.3482 | 14.0 | 8260 | 2.3764 | 0.6572 | |
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| 2.3162 | 15.0 | 8850 | 2.1363 | 0.6489 | |
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| 2.1908 | 16.0 | 9440 | 3.3056 | 0.6407 | |
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| 2.0964 | 17.0 | 10030 | 2.3744 | 0.6489 | |
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| 2.063 | 18.0 | 10620 | 2.3019 | 0.6021 | |
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| 2.0119 | 19.0 | 11210 | 2.0892 | 0.6734 | |
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| 2.0429 | 20.0 | 11800 | 2.5552 | 0.6596 | |
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| 1.9324 | 21.0 | 12390 | 2.0537 | 0.6694 | |
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| 1.9379 | 22.0 | 12980 | 1.9183 | 0.6801 | |
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| 1.9294 | 23.0 | 13570 | 1.8407 | 0.6774 | |
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| 1.8366 | 24.0 | 14160 | 1.8770 | 0.6872 | |
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| 1.809 | 25.0 | 14750 | 2.0356 | 0.6761 | |
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| 1.804 | 26.0 | 15340 | 1.6646 | 0.6801 | |
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| 1.8059 | 27.0 | 15930 | 1.6864 | 0.6780 | |
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| 1.7665 | 28.0 | 16520 | 1.6191 | 0.6813 | |
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| 1.7034 | 29.0 | 17110 | 1.8237 | 0.6477 | |
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| 1.663 | 30.0 | 17700 | 1.5530 | 0.6911 | |
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| 1.619 | 31.0 | 18290 | 1.5786 | 0.6884 | |
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| 1.5861 | 32.0 | 18880 | 2.2685 | 0.6746 | |
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| 1.5504 | 33.0 | 19470 | 1.6077 | 0.6624 | |
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| 1.5419 | 34.0 | 20060 | 1.4337 | 0.6976 | |
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| 1.5614 | 35.0 | 20650 | 1.5165 | 0.6969 | |
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| 1.5039 | 36.0 | 21240 | 1.8150 | 0.6972 | |
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| 1.4848 | 37.0 | 21830 | 1.3947 | 0.7006 | |
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| 1.4697 | 38.0 | 22420 | 1.5730 | 0.6709 | |
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| 1.3728 | 39.0 | 23010 | 1.5815 | 0.7021 | |
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| 1.4163 | 40.0 | 23600 | 1.3688 | 0.7125 | |
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| 1.3908 | 41.0 | 24190 | 1.5884 | 0.7006 | |
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| 1.3566 | 42.0 | 24780 | 1.3154 | 0.7180 | |
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| 1.3155 | 43.0 | 25370 | 1.2954 | 0.7138 | |
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| 1.3059 | 44.0 | 25960 | 1.2546 | 0.7116 | |
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| 1.2942 | 45.0 | 26550 | 1.4254 | 0.7092 | |
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| 1.2492 | 46.0 | 27140 | 1.2366 | 0.7180 | |
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| 1.2493 | 47.0 | 27730 | 1.2187 | 0.7095 | |
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| 1.202 | 48.0 | 28320 | 1.2318 | 0.7183 | |
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| 1.2327 | 49.0 | 28910 | 1.4508 | 0.7083 | |
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| 1.215 | 50.0 | 29500 | 1.2490 | 0.7205 | |
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| 1.1485 | 51.0 | 30090 | 1.3040 | 0.7147 | |
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| 1.157 | 52.0 | 30680 | 1.1436 | 0.7180 | |
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| 1.1302 | 53.0 | 31270 | 1.1814 | 0.7147 | |
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| 1.1111 | 54.0 | 31860 | 1.3464 | 0.7150 | |
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| 1.1422 | 55.0 | 32450 | 1.3631 | 0.7144 | |
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| 1.0891 | 56.0 | 33040 | 1.1418 | 0.7214 | |
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| 1.0652 | 57.0 | 33630 | 1.2196 | 0.7202 | |
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| 1.0556 | 58.0 | 34220 | 1.2335 | 0.7235 | |
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| 1.0672 | 59.0 | 34810 | 1.1583 | 0.7128 | |
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| 1.0613 | 60.0 | 35400 | 1.1927 | 0.7061 | |
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| 1.0069 | 61.0 | 35990 | 1.0860 | 0.7226 | |
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| 1.0483 | 62.0 | 36580 | 1.1060 | 0.7245 | |
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| 1.0051 | 63.0 | 37170 | 1.1095 | 0.7150 | |
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| 0.9834 | 64.0 | 37760 | 1.0793 | 0.7196 | |
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| 0.9801 | 65.0 | 38350 | 1.1033 | 0.7196 | |
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| 0.9647 | 66.0 | 38940 | 1.0704 | 0.7214 | |
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| 0.9384 | 67.0 | 39530 | 1.0795 | 0.7196 | |
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| 0.9791 | 68.0 | 40120 | 1.1657 | 0.7245 | |
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| 0.9309 | 69.0 | 40710 | 1.1983 | 0.7263 | |
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| 0.9602 | 70.0 | 41300 | 1.1575 | 0.7284 | |
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| 0.9462 | 71.0 | 41890 | 1.0949 | 0.7165 | |
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| 0.9473 | 72.0 | 42480 | 1.1855 | 0.7266 | |
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| 0.9047 | 73.0 | 43070 | 1.1378 | 0.7266 | |
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| 0.8996 | 74.0 | 43660 | 1.0339 | 0.7226 | |
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| 0.9248 | 75.0 | 44250 | 1.1656 | 0.7309 | |
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| 0.9075 | 76.0 | 44840 | 1.0272 | 0.7208 | |
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| 0.9062 | 77.0 | 45430 | 1.1646 | 0.7327 | |
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| 0.8987 | 78.0 | 46020 | 1.0606 | 0.7202 | |
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| 0.8831 | 79.0 | 46610 | 1.0543 | 0.7291 | |
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| 0.8655 | 80.0 | 47200 | 1.0785 | 0.7312 | |
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| 0.8629 | 81.0 | 47790 | 1.0745 | 0.7284 | |
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| 0.8733 | 82.0 | 48380 | 1.0734 | 0.7242 | |
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| 0.8796 | 83.0 | 48970 | 1.0343 | 0.7266 | |
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| 0.8313 | 84.0 | 49560 | 1.0709 | 0.7294 | |
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| 0.835 | 85.0 | 50150 | 1.0230 | 0.7266 | |
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| 0.8425 | 86.0 | 50740 | 1.0049 | 0.7235 | |
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| 0.8486 | 87.0 | 51330 | 1.0971 | 0.7278 | |
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| 0.8361 | 88.0 | 51920 | 1.0212 | 0.7226 | |
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| 0.8171 | 89.0 | 52510 | 1.1451 | 0.7287 | |
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| 0.7994 | 90.0 | 53100 | 1.0329 | 0.7315 | |
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| 0.8268 | 91.0 | 53690 | 1.0968 | 0.7346 | |
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| 0.8289 | 92.0 | 54280 | 1.0031 | 0.7223 | |
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| 0.8082 | 93.0 | 54870 | 1.0499 | 0.7278 | |
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| 0.8188 | 94.0 | 55460 | 1.0121 | 0.7235 | |
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| 0.82 | 95.0 | 56050 | 1.0232 | 0.7242 | |
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| 0.8028 | 96.0 | 56640 | 1.0279 | 0.7229 | |
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| 0.7891 | 97.0 | 57230 | 1.0091 | 0.7260 | |
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| 0.7771 | 98.0 | 57820 | 1.0230 | 0.7248 | |
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| 0.7652 | 99.0 | 58410 | 1.0248 | 0.7257 | |
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| 0.7874 | 100.0 | 59000 | 1.0161 | 0.7254 | |
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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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