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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: 2_5e-3_10_0.5 |
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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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# 2_5e-3_10_0.5 |
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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: 0.8743 |
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- Accuracy: 0.7407 |
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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: 60.0 |
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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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| 2.0951 | 1.0 | 590 | 2.8478 | 0.6208 | |
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| 2.0966 | 2.0 | 1180 | 2.0402 | 0.6208 | |
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| 1.9864 | 3.0 | 1770 | 2.9563 | 0.4196 | |
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| 1.9962 | 4.0 | 2360 | 2.4148 | 0.4905 | |
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| 1.8743 | 5.0 | 2950 | 2.1057 | 0.6217 | |
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| 1.562 | 6.0 | 3540 | 1.6253 | 0.6636 | |
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| 1.4913 | 7.0 | 4130 | 1.4832 | 0.6734 | |
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| 1.4114 | 8.0 | 4720 | 1.4386 | 0.6560 | |
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| 1.3732 | 9.0 | 5310 | 1.4139 | 0.6508 | |
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| 1.3161 | 10.0 | 5900 | 1.3009 | 0.6893 | |
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| 1.2979 | 11.0 | 6490 | 1.2760 | 0.6963 | |
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| 1.1837 | 12.0 | 7080 | 1.2606 | 0.6737 | |
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| 1.2171 | 13.0 | 7670 | 1.2241 | 0.7040 | |
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| 1.1545 | 14.0 | 8260 | 1.2533 | 0.7086 | |
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| 1.1424 | 15.0 | 8850 | 1.1613 | 0.7061 | |
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| 1.1106 | 16.0 | 9440 | 1.1290 | 0.7018 | |
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| 1.0798 | 17.0 | 10030 | 1.1366 | 0.7049 | |
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| 1.0665 | 18.0 | 10620 | 1.1030 | 0.7147 | |
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| 1.0642 | 19.0 | 11210 | 1.1100 | 0.7168 | |
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| 1.0498 | 20.0 | 11800 | 1.1124 | 0.7235 | |
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| 0.9966 | 21.0 | 12390 | 1.1192 | 0.7211 | |
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| 1.0178 | 22.0 | 12980 | 1.0786 | 0.7211 | |
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| 0.9956 | 23.0 | 13570 | 1.0710 | 0.7024 | |
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| 0.9896 | 24.0 | 14160 | 1.0254 | 0.7211 | |
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| 0.9496 | 25.0 | 14750 | 1.0181 | 0.7217 | |
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| 0.9755 | 26.0 | 15340 | 1.0013 | 0.7211 | |
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| 0.9439 | 27.0 | 15930 | 1.0014 | 0.7153 | |
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| 0.9151 | 28.0 | 16520 | 0.9923 | 0.7336 | |
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| 0.8988 | 29.0 | 17110 | 0.9776 | 0.7318 | |
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| 0.8962 | 30.0 | 17700 | 0.9625 | 0.7401 | |
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| 0.8825 | 31.0 | 18290 | 0.9702 | 0.7346 | |
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| 0.8734 | 32.0 | 18880 | 0.9766 | 0.7394 | |
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| 0.8651 | 33.0 | 19470 | 0.9443 | 0.7394 | |
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| 0.8404 | 34.0 | 20060 | 0.9665 | 0.7364 | |
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| 0.8312 | 35.0 | 20650 | 0.9290 | 0.7370 | |
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| 0.8401 | 36.0 | 21240 | 0.9546 | 0.7309 | |
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| 0.8121 | 37.0 | 21830 | 0.9287 | 0.7391 | |
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| 0.8162 | 38.0 | 22420 | 0.9171 | 0.7278 | |
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| 0.8096 | 39.0 | 23010 | 0.9196 | 0.7428 | |
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| 0.7901 | 40.0 | 23600 | 0.9168 | 0.7422 | |
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| 0.8011 | 41.0 | 24190 | 0.9136 | 0.7297 | |
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| 0.7908 | 42.0 | 24780 | 0.9080 | 0.7385 | |
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| 0.7755 | 43.0 | 25370 | 0.9270 | 0.7446 | |
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| 0.786 | 44.0 | 25960 | 0.8954 | 0.7333 | |
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| 0.7664 | 45.0 | 26550 | 0.9038 | 0.7410 | |
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| 0.7725 | 46.0 | 27140 | 0.8874 | 0.7431 | |
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| 0.7607 | 47.0 | 27730 | 0.9019 | 0.7416 | |
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| 0.7683 | 48.0 | 28320 | 0.9069 | 0.7456 | |
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| 0.7594 | 49.0 | 28910 | 0.9003 | 0.7318 | |
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| 0.7317 | 50.0 | 29500 | 0.8860 | 0.7428 | |
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| 0.7306 | 51.0 | 30090 | 0.8862 | 0.7434 | |
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| 0.736 | 52.0 | 30680 | 0.8952 | 0.7471 | |
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| 0.7343 | 53.0 | 31270 | 0.8761 | 0.7419 | |
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| 0.7248 | 54.0 | 31860 | 0.8876 | 0.7309 | |
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| 0.7334 | 55.0 | 32450 | 0.8841 | 0.7431 | |
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| 0.7458 | 56.0 | 33040 | 0.8817 | 0.7434 | |
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| 0.727 | 57.0 | 33630 | 0.8743 | 0.7431 | |
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| 0.7077 | 58.0 | 34220 | 0.8741 | 0.7422 | |
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| 0.7158 | 59.0 | 34810 | 0.8768 | 0.7446 | |
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| 0.7061 | 60.0 | 35400 | 0.8743 | 0.7407 | |
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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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