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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: '20230831092825' |
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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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# 20230831092825 |
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This model is a fine-tuned version of [bert-large-cased](https://huggingface.co/bert-large-cased) on the super_glue dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5298 |
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- Accuracy: 0.6771 |
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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: 0.0003 |
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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: 80.0 |
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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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| No log | 1.0 | 340 | 0.4989 | 0.5 | |
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| 0.5076 | 2.0 | 680 | 0.4922 | 0.5 | |
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| 0.5029 | 3.0 | 1020 | 0.4980 | 0.5 | |
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| 0.5029 | 4.0 | 1360 | 0.4881 | 0.5125 | |
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| 0.4992 | 5.0 | 1700 | 0.5067 | 0.5 | |
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| 0.4818 | 6.0 | 2040 | 0.4919 | 0.5251 | |
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| 0.4818 | 7.0 | 2380 | 0.5045 | 0.5392 | |
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| 0.4719 | 8.0 | 2720 | 0.4695 | 0.5 | |
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| 0.4636 | 9.0 | 3060 | 0.4805 | 0.5 | |
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| 0.4636 | 10.0 | 3400 | 0.5002 | 0.5 | |
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| 0.4501 | 11.0 | 3740 | 0.5665 | 0.6646 | |
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| 0.4418 | 12.0 | 4080 | 0.5283 | 0.6897 | |
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| 0.4418 | 13.0 | 4420 | 0.4705 | 0.5 | |
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| 0.4352 | 14.0 | 4760 | 0.5644 | 0.6630 | |
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| 0.4302 | 15.0 | 5100 | 0.5080 | 0.6505 | |
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| 0.4302 | 16.0 | 5440 | 0.5084 | 0.6897 | |
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| 0.4305 | 17.0 | 5780 | 0.5006 | 0.6599 | |
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| 0.4203 | 18.0 | 6120 | 0.5246 | 0.6928 | |
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| 0.4203 | 19.0 | 6460 | 0.4958 | 0.6583 | |
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| 0.4166 | 20.0 | 6800 | 0.5595 | 0.6630 | |
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| 0.4117 | 21.0 | 7140 | 0.4796 | 0.5 | |
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| 0.4117 | 22.0 | 7480 | 0.4820 | 0.5 | |
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| 0.4131 | 23.0 | 7820 | 0.5158 | 0.6755 | |
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| 0.406 | 24.0 | 8160 | 0.4801 | 0.5 | |
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| 0.4062 | 25.0 | 8500 | 0.5471 | 0.6646 | |
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| 0.4062 | 26.0 | 8840 | 0.4904 | 0.5 | |
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| 0.4021 | 27.0 | 9180 | 0.4880 | 0.5 | |
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| 0.3971 | 28.0 | 9520 | 0.5019 | 0.6646 | |
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| 0.3971 | 29.0 | 9860 | 0.4825 | 0.5 | |
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| 0.3936 | 30.0 | 10200 | 0.5069 | 0.6693 | |
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| 0.3907 | 31.0 | 10540 | 0.5472 | 0.6693 | |
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| 0.3907 | 32.0 | 10880 | 0.4886 | 0.5 | |
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| 0.3906 | 33.0 | 11220 | 0.5531 | 0.6693 | |
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| 0.3888 | 34.0 | 11560 | 0.5023 | 0.5266 | |
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| 0.3888 | 35.0 | 11900 | 0.4896 | 0.5 | |
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| 0.387 | 36.0 | 12240 | 0.4985 | 0.5 | |
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| 0.3836 | 37.0 | 12580 | 0.5309 | 0.6834 | |
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| 0.3836 | 38.0 | 12920 | 0.5402 | 0.6818 | |
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| 0.3792 | 39.0 | 13260 | 0.4854 | 0.5 | |
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| 0.3789 | 40.0 | 13600 | 0.4971 | 0.5 | |
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| 0.3789 | 41.0 | 13940 | 0.5368 | 0.6803 | |
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| 0.3775 | 42.0 | 14280 | 0.4958 | 0.5047 | |
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| 0.3753 | 43.0 | 14620 | 0.5139 | 0.6897 | |
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| 0.3753 | 44.0 | 14960 | 0.5224 | 0.6834 | |
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| 0.3795 | 45.0 | 15300 | 0.5119 | 0.6865 | |
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| 0.3743 | 46.0 | 15640 | 0.5120 | 0.6740 | |
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| 0.3743 | 47.0 | 15980 | 0.5049 | 0.5204 | |
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| 0.3726 | 48.0 | 16320 | 0.5026 | 0.5 | |
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| 0.3683 | 49.0 | 16660 | 0.5137 | 0.6646 | |
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| 0.3707 | 50.0 | 17000 | 0.5088 | 0.6129 | |
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| 0.3707 | 51.0 | 17340 | 0.5608 | 0.6646 | |
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| 0.3654 | 52.0 | 17680 | 0.5217 | 0.6803 | |
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| 0.3684 | 53.0 | 18020 | 0.5236 | 0.6740 | |
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| 0.3684 | 54.0 | 18360 | 0.5135 | 0.5016 | |
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| 0.3663 | 55.0 | 18700 | 0.5192 | 0.6818 | |
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| 0.3669 | 56.0 | 19040 | 0.5212 | 0.6160 | |
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| 0.3669 | 57.0 | 19380 | 0.5320 | 0.6740 | |
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| 0.3641 | 58.0 | 19720 | 0.5344 | 0.6646 | |
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| 0.3628 | 59.0 | 20060 | 0.4991 | 0.5 | |
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| 0.3628 | 60.0 | 20400 | 0.5341 | 0.6661 | |
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| 0.3612 | 61.0 | 20740 | 0.5039 | 0.5 | |
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| 0.3608 | 62.0 | 21080 | 0.5267 | 0.6379 | |
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| 0.3608 | 63.0 | 21420 | 0.5249 | 0.6364 | |
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| 0.3599 | 64.0 | 21760 | 0.5226 | 0.6599 | |
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| 0.3616 | 65.0 | 22100 | 0.5370 | 0.6834 | |
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| 0.3616 | 66.0 | 22440 | 0.5109 | 0.5 | |
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| 0.3543 | 67.0 | 22780 | 0.5368 | 0.6740 | |
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| 0.3616 | 68.0 | 23120 | 0.5236 | 0.5690 | |
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| 0.3616 | 69.0 | 23460 | 0.5300 | 0.6693 | |
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| 0.3578 | 70.0 | 23800 | 0.5441 | 0.6583 | |
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| 0.3541 | 71.0 | 24140 | 0.5310 | 0.6724 | |
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| 0.3541 | 72.0 | 24480 | 0.5346 | 0.6693 | |
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| 0.354 | 73.0 | 24820 | 0.5338 | 0.6630 | |
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| 0.355 | 74.0 | 25160 | 0.5279 | 0.6599 | |
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| 0.3536 | 75.0 | 25500 | 0.5280 | 0.6552 | |
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| 0.3536 | 76.0 | 25840 | 0.5328 | 0.6693 | |
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| 0.3539 | 77.0 | 26180 | 0.5231 | 0.5376 | |
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| 0.3527 | 78.0 | 26520 | 0.5282 | 0.6646 | |
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| 0.3527 | 79.0 | 26860 | 0.5250 | 0.6364 | |
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| 0.3535 | 80.0 | 27200 | 0.5298 | 0.6771 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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