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BioHackathon_Lipids-tapt_ulmfit-LR_2e-05

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  1. README.md +161 -0
  2. config.json +25 -0
  3. generation_config.json +5 -0
  4. model.safetensors +3 -0
  5. special_tokens_map.json +7 -0
  6. tokenizer.json +0 -0
  7. tokenizer_config.json +58 -0
  8. training_args.bin +3 -0
  9. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: mit
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+ base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
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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: BioHackathon_Lipids-tapt_ulmfit-LR_2e-05
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+ results: []
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+ ---
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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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+
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+ # BioHackathon_Lipids-tapt_ulmfit-LR_2e-05
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+
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+ This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0089
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+ - Accuracy: 0.7719
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 16
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+ - eval_batch_size: 16
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+ - seed: 3407
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.06
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+ - num_epochs: 100
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | 1.1173 | 1.0 | 29 | 1.0719 | 0.7634 |
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+ | 1.1305 | 2.0 | 58 | 1.0794 | 0.7616 |
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+ | 1.1273 | 3.0 | 87 | 1.0206 | 0.7735 |
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+ | 1.1235 | 4.0 | 116 | 1.0500 | 0.7668 |
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+ | 1.1148 | 5.0 | 145 | 1.0672 | 0.7624 |
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+ | 1.0937 | 6.0 | 174 | 1.0456 | 0.7704 |
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+ | 1.0873 | 7.0 | 203 | 1.0653 | 0.7674 |
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+ | 1.0914 | 8.0 | 232 | 1.0253 | 0.7688 |
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+ | 1.1042 | 9.0 | 261 | 1.0706 | 0.7635 |
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+ | 1.0698 | 10.0 | 290 | 1.0236 | 0.7744 |
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+ | 1.0837 | 11.0 | 319 | 1.0653 | 0.7632 |
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+ | 1.0862 | 12.0 | 348 | 1.0166 | 0.7745 |
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+ | 1.0699 | 13.0 | 377 | 1.0374 | 0.7684 |
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+ | 1.0775 | 14.0 | 406 | 1.0149 | 0.7752 |
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+ | 1.0512 | 15.0 | 435 | 1.0393 | 0.7689 |
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+ | 1.0781 | 16.0 | 464 | 1.0280 | 0.7692 |
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+ | 1.0683 | 17.0 | 493 | 1.0156 | 0.7726 |
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+ | 1.0821 | 18.0 | 522 | 1.0366 | 0.7750 |
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+ | 1.0543 | 19.0 | 551 | 1.0215 | 0.7729 |
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+ | 1.0674 | 20.0 | 580 | 1.0010 | 0.7736 |
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+ | 1.0628 | 21.0 | 609 | 1.0159 | 0.7682 |
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+ | 1.0622 | 22.0 | 638 | 1.0183 | 0.7691 |
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+ | 1.0399 | 23.0 | 667 | 1.0685 | 0.7654 |
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+ | 1.0301 | 24.0 | 696 | 1.0431 | 0.7718 |
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+ | 1.0517 | 25.0 | 725 | 1.0105 | 0.7746 |
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+ | 1.0529 | 26.0 | 754 | 0.9985 | 0.7732 |
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+ | 1.0448 | 27.0 | 783 | 1.0250 | 0.7685 |
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+ | 1.036 | 28.0 | 812 | 1.0129 | 0.7674 |
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+ | 1.0334 | 29.0 | 841 | 1.0039 | 0.7743 |
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+ | 1.0279 | 30.0 | 870 | 1.0235 | 0.7717 |
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+ | 1.031 | 31.0 | 899 | 1.0073 | 0.7719 |
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+ | 1.0038 | 32.0 | 928 | 1.0215 | 0.7662 |
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+ | 1.0077 | 33.0 | 957 | 1.0471 | 0.7674 |
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+ | 1.0056 | 34.0 | 986 | 1.0235 | 0.7707 |
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+ | 1.0017 | 35.0 | 1015 | 0.9899 | 0.7729 |
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+ | 0.9885 | 36.0 | 1044 | 1.0062 | 0.7753 |
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+ | 1.0057 | 37.0 | 1073 | 1.0204 | 0.7703 |
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+ | 1.0062 | 38.0 | 1102 | 1.0028 | 0.7709 |
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+ | 0.9956 | 39.0 | 1131 | 1.0575 | 0.7602 |
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+ | 1.0014 | 40.0 | 1160 | 1.0122 | 0.7745 |
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+ | 0.997 | 41.0 | 1189 | 1.0124 | 0.7721 |
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+ | 0.9741 | 42.0 | 1218 | 1.0455 | 0.7637 |
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+ | 0.9816 | 43.0 | 1247 | 1.0390 | 0.7677 |
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+ | 0.9899 | 44.0 | 1276 | 1.0734 | 0.7593 |
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+ | 0.9707 | 45.0 | 1305 | 1.0267 | 0.7700 |
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+ | 0.9705 | 46.0 | 1334 | 1.0408 | 0.7726 |
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+ | 0.9663 | 47.0 | 1363 | 1.0350 | 0.7679 |
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+ | 0.9914 | 48.0 | 1392 | 1.0182 | 0.7686 |
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+ | 0.9909 | 49.0 | 1421 | 1.0218 | 0.7664 |
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+ | 0.9678 | 50.0 | 1450 | 1.0417 | 0.7709 |
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+ | 0.964 | 51.0 | 1479 | 1.0112 | 0.7733 |
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+ | 0.9655 | 52.0 | 1508 | 1.0314 | 0.7666 |
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+ | 0.9735 | 53.0 | 1537 | 1.0200 | 0.7702 |
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+ | 0.9624 | 54.0 | 1566 | 1.0394 | 0.7682 |
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+ | 0.951 | 55.0 | 1595 | 1.0211 | 0.7697 |
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+ | 0.9664 | 56.0 | 1624 | 1.0353 | 0.7706 |
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+ | 0.9449 | 57.0 | 1653 | 1.0195 | 0.7726 |
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+ | 0.9464 | 58.0 | 1682 | 1.0432 | 0.7644 |
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+ | 0.9477 | 59.0 | 1711 | 1.0151 | 0.7701 |
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+ | 0.9381 | 60.0 | 1740 | 0.9901 | 0.7765 |
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+ | 0.9442 | 61.0 | 1769 | 1.0175 | 0.7673 |
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+ | 0.9364 | 62.0 | 1798 | 1.0653 | 0.7639 |
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+ | 0.9405 | 63.0 | 1827 | 1.0308 | 0.7651 |
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+ | 0.9498 | 64.0 | 1856 | 1.0132 | 0.7727 |
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+ | 0.9372 | 65.0 | 1885 | 1.0252 | 0.7729 |
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+ | 0.9356 | 66.0 | 1914 | 1.0254 | 0.7664 |
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+ | 0.9383 | 67.0 | 1943 | 0.9812 | 0.7742 |
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+ | 0.9336 | 68.0 | 1972 | 1.0125 | 0.7712 |
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+ | 0.9362 | 69.0 | 2001 | 1.0397 | 0.7631 |
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+ | 0.9273 | 70.0 | 2030 | 1.0128 | 0.7671 |
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+ | 0.933 | 71.0 | 2059 | 1.0381 | 0.7659 |
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+ | 0.9418 | 72.0 | 2088 | 1.0013 | 0.7722 |
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+ | 0.952 | 73.0 | 2117 | 1.0078 | 0.7724 |
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+ | 0.9204 | 74.0 | 2146 | 1.0435 | 0.7721 |
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+ | 0.9186 | 75.0 | 2175 | 1.0336 | 0.7704 |
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+ | 0.9303 | 76.0 | 2204 | 1.0415 | 0.7704 |
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+ | 0.9376 | 77.0 | 2233 | 1.0153 | 0.7772 |
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+ | 0.9168 | 78.0 | 2262 | 1.0177 | 0.7689 |
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+ | 0.9211 | 79.0 | 2291 | 1.0094 | 0.7752 |
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+ | 0.9527 | 80.0 | 2320 | 0.9772 | 0.7762 |
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+ | 0.9262 | 81.0 | 2349 | 1.0733 | 0.7675 |
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+ | 0.9366 | 82.0 | 2378 | 1.0236 | 0.7707 |
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+ | 0.9174 | 83.0 | 2407 | 1.0249 | 0.7679 |
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+ | 0.9156 | 84.0 | 2436 | 1.0120 | 0.7689 |
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+ | 0.933 | 85.0 | 2465 | 1.0519 | 0.7647 |
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+ | 0.9294 | 86.0 | 2494 | 1.0183 | 0.7701 |
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+ | 0.928 | 87.0 | 2523 | 1.0252 | 0.7660 |
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+ | 0.9202 | 88.0 | 2552 | 1.0469 | 0.7644 |
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+ | 0.9081 | 89.0 | 2581 | 1.0259 | 0.7707 |
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+ | 0.9164 | 90.0 | 2610 | 1.0298 | 0.7666 |
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+ | 0.9215 | 91.0 | 2639 | 1.0293 | 0.7710 |
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+ | 0.9258 | 92.0 | 2668 | 1.0461 | 0.7634 |
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+ | 0.9052 | 93.0 | 2697 | 1.0126 | 0.7721 |
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+ | 0.9322 | 94.0 | 2726 | 1.0077 | 0.7741 |
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+ | 0.9144 | 95.0 | 2755 | 1.0300 | 0.7671 |
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+ | 0.9204 | 96.0 | 2784 | 1.0631 | 0.7628 |
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+ | 0.9323 | 96.5614 | 2800 | 1.0089 | 0.7719 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.2
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+ - Tokenizers 0.21.0
config.json ADDED
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