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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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metrics: |
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- accuracy |
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model-index: |
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- name: claim-judge |
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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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# claim-judge |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.7623 |
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- Loss: 1.5465 |
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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: 2e-05 |
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- train_batch_size: 160 |
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- eval_batch_size: 160 |
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- seed: 42 |
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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: 36 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:-----:|:--------:|:---------------:| |
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| 0.4968 | 1.0 | 1041 | 0.7587 | 0.6138 | |
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| 0.4174 | 2.0 | 2082 | 0.7695 | 0.6211 | |
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| 0.4036 | 3.0 | 3123 | 0.7733 | 0.6181 | |
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| 0.3415 | 4.0 | 4164 | 0.7772 | 0.6450 | |
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| 0.2868 | 5.0 | 5205 | 0.7738 | 0.6896 | |
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| 0.2453 | 6.0 | 6246 | 0.7763 | 0.7119 | |
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| 0.2003 | 7.0 | 7287 | 0.7728 | 0.8254 | |
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| 0.1683 | 8.0 | 8328 | 0.7712 | 0.9288 | |
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| 0.1439 | 9.0 | 9369 | 0.7764 | 0.8993 | |
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| 0.1197 | 10.0 | 10410 | 0.7729 | 0.9819 | |
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| 0.102 | 11.0 | 11451 | 0.7709 | 1.0478 | |
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| 0.088 | 12.0 | 12492 | 0.7692 | 1.1574 | |
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| 0.087 | 13.0 | 13533 | 0.7709 | 1.0969 | |
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| 0.0779 | 14.0 | 14574 | 0.7661 | 1.2575 | |
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| 0.0695 | 15.0 | 15615 | 0.7658 | 1.3540 | |
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| 0.0664 | 16.0 | 16656 | 0.7719 | 1.2155 | |
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| 0.058 | 17.0 | 17697 | 0.7654 | 1.3065 | |
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| 0.0533 | 18.0 | 18738 | 0.7674 | 1.3535 | |
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| 0.0496 | 19.0 | 19779 | 0.7663 | 1.3327 | |
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| 0.0459 | 20.0 | 20820 | 0.7686 | 1.3893 | |
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| 0.0432 | 21.0 | 21861 | 0.7691 | 1.4211 | |
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| 0.0396 | 22.0 | 22902 | 0.7682 | 1.4810 | |
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| 0.0371 | 23.0 | 23943 | 0.7705 | 1.4926 | |
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| 0.0338 | 24.0 | 24984 | 0.7633 | 1.5058 | |
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| 0.037 | 25.0 | 26025 | 0.7604 | 1.4986 | |
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| 0.034 | 26.0 | 27066 | 0.7611 | 1.5314 | |
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| 0.0317 | 27.0 | 28107 | 0.7659 | 1.4636 | |
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| 0.0312 | 28.0 | 29148 | 0.7658 | 1.5006 | |
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| 0.0282 | 29.0 | 30189 | 0.7672 | 1.4250 | |
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| 0.0282 | 30.0 | 31230 | 0.7662 | 1.4904 | |
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| 0.0264 | 31.0 | 32271 | 0.7669 | 1.5415 | |
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| 0.0253 | 32.0 | 33312 | 0.7679 | 1.6110 | |
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| 0.0257 | 33.0 | 34353 | 0.7645 | 1.6097 | |
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| 0.0233 | 34.0 | 35394 | 0.7614 | 1.6646 | |
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| 0.0251 | 35.0 | 36435 | 0.7651 | 1.6080 | |
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| 0.0236 | 36.0 | 37476 | 0.7699 | 1.5824 | |
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| 0.025 | 37.0 | 38517 | 0.7623 | 1.5465 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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