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PassbyGrocer
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hreb-resume

Token Classification
Transformers
Safetensors
bert
Generated from Trainer
Inference Endpoints
Model card Files Community
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End of training

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Files changed (8) hide show
  1. README.md +166 -0
  2. config.json +72 -0
  3. model.safetensors +3 -0
  4. special_tokens_map.json +37 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +55 -0
  7. training_args.bin +3 -0
  8. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: hfl/chinese-roberta-wwm-ext-large
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: robert_bilstm_mega_res-ner-resume-ner
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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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+ # robert_bilstm_mega_res-ner-resume-ner
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+
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+ This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2110
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+ - Precision: 0.9394
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+ - Recall: 0.9582
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+ - F1: 0.9487
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+ - Accuracy: 0.9817
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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: 5e-05
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0676 | 1.0 | 120 | 0.0879 | 0.8905 | 0.9464 | 0.9176 | 0.9751 |
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+ | 0.0751 | 2.0 | 240 | 0.0774 | 0.9136 | 0.9518 | 0.9323 | 0.9796 |
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+ | 0.0342 | 3.0 | 360 | 0.0889 | 0.9198 | 0.9591 | 0.9390 | 0.9807 |
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+ | 0.0261 | 4.0 | 480 | 0.1041 | 0.9317 | 0.9555 | 0.9434 | 0.9809 |
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+ | 0.0082 | 5.0 | 600 | 0.1255 | 0.9308 | 0.9536 | 0.9421 | 0.9802 |
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+ | 0.0134 | 6.0 | 720 | 0.1389 | 0.9286 | 0.9573 | 0.9427 | 0.9793 |
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+ | 0.0089 | 7.0 | 840 | 0.1369 | 0.9366 | 0.9536 | 0.9450 | 0.9798 |
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+ | 0.0093 | 8.0 | 960 | 0.1272 | 0.9393 | 0.9564 | 0.9477 | 0.9815 |
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+ | 0.0044 | 9.0 | 1080 | 0.1384 | 0.9332 | 0.9518 | 0.9424 | 0.9803 |
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+ | 0.0017 | 10.0 | 1200 | 0.1662 | 0.9401 | 0.9564 | 0.9482 | 0.9788 |
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+ | 0.001 | 11.0 | 1320 | 0.1569 | 0.9368 | 0.9564 | 0.9465 | 0.9801 |
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+ | 0.0007 | 12.0 | 1440 | 0.1724 | 0.9384 | 0.9564 | 0.9473 | 0.9801 |
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+ | 0.0017 | 13.0 | 1560 | 0.1794 | 0.9291 | 0.9536 | 0.9412 | 0.9790 |
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+ | 0.0004 | 14.0 | 1680 | 0.1716 | 0.9325 | 0.9545 | 0.9434 | 0.9795 |
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+ | 0.0027 | 15.0 | 1800 | 0.1679 | 0.9435 | 0.9573 | 0.9504 | 0.9807 |
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+ | 0.0048 | 16.0 | 1920 | 0.1753 | 0.9401 | 0.9564 | 0.9482 | 0.9800 |
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+ | 0.001 | 17.0 | 2040 | 0.1872 | 0.9359 | 0.9564 | 0.9460 | 0.9793 |
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+ | 0.0009 | 18.0 | 2160 | 0.1851 | 0.9453 | 0.9582 | 0.9517 | 0.9798 |
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+ | 0.0067 | 19.0 | 2280 | 0.1645 | 0.9461 | 0.9582 | 0.9521 | 0.9805 |
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+ | 0.0002 | 20.0 | 2400 | 0.1712 | 0.9352 | 0.9573 | 0.9461 | 0.9798 |
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+ | 0.0023 | 21.0 | 2520 | 0.1779 | 0.9412 | 0.96 | 0.9505 | 0.9805 |
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+ | 0.0001 | 22.0 | 2640 | 0.1804 | 0.9402 | 0.9582 | 0.9491 | 0.9806 |
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+ | 0.0002 | 23.0 | 2760 | 0.1868 | 0.9386 | 0.9591 | 0.9487 | 0.9808 |
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+ | 0.0017 | 24.0 | 2880 | 0.1742 | 0.9358 | 0.9545 | 0.9451 | 0.9811 |
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+ | 0.0006 | 25.0 | 3000 | 0.1792 | 0.9452 | 0.9573 | 0.9512 | 0.9818 |
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+ | 0.0011 | 26.0 | 3120 | 0.1801 | 0.9265 | 0.9518 | 0.9390 | 0.9778 |
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+ | 0.0002 | 27.0 | 3240 | 0.2164 | 0.9402 | 0.9582 | 0.9491 | 0.9783 |
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+ | 0.0001 | 28.0 | 3360 | 0.1851 | 0.9425 | 0.9545 | 0.9485 | 0.9821 |
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+ | 0.0001 | 29.0 | 3480 | 0.1889 | 0.9417 | 0.9545 | 0.9481 | 0.9813 |
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+ | 0.0005 | 30.0 | 3600 | 0.1914 | 0.9460 | 0.9564 | 0.9512 | 0.9804 |
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+ | 0.0023 | 31.0 | 3720 | 0.1854 | 0.9497 | 0.9609 | 0.9553 | 0.9823 |
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+ | 0.0004 | 32.0 | 3840 | 0.1883 | 0.9409 | 0.9545 | 0.9477 | 0.9807 |
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+ | 0.0005 | 33.0 | 3960 | 0.1789 | 0.9470 | 0.9591 | 0.9530 | 0.9819 |
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+ | 0.0002 | 34.0 | 4080 | 0.2061 | 0.9453 | 0.9582 | 0.9517 | 0.9802 |
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+ | 0.0001 | 35.0 | 4200 | 0.1968 | 0.9479 | 0.9591 | 0.9535 | 0.9812 |
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+ | 0.0001 | 36.0 | 4320 | 0.2021 | 0.9479 | 0.9591 | 0.9535 | 0.9813 |
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+ | 0.0002 | 37.0 | 4440 | 0.2001 | 0.9437 | 0.96 | 0.9518 | 0.9812 |
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+ | 0.0016 | 38.0 | 4560 | 0.1796 | 0.9340 | 0.9518 | 0.9428 | 0.9805 |
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+ | 0.0001 | 39.0 | 4680 | 0.1759 | 0.9461 | 0.9582 | 0.9521 | 0.9806 |
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+ | 0.0017 | 40.0 | 4800 | 0.1789 | 0.9462 | 0.96 | 0.9531 | 0.9816 |
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+ | 0.0053 | 41.0 | 4920 | 0.1794 | 0.9436 | 0.9591 | 0.9513 | 0.9816 |
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+ | 0.0 | 42.0 | 5040 | 0.1849 | 0.9418 | 0.9555 | 0.9486 | 0.9814 |
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+ | 0.0 | 43.0 | 5160 | 0.1888 | 0.9453 | 0.9582 | 0.9517 | 0.9814 |
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+ | 0.0001 | 44.0 | 5280 | 0.1972 | 0.9340 | 0.9527 | 0.9433 | 0.9788 |
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+ | 0.0001 | 45.0 | 5400 | 0.1898 | 0.9400 | 0.9545 | 0.9472 | 0.9793 |
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+ | 0.001 | 46.0 | 5520 | 0.1926 | 0.9392 | 0.9545 | 0.9468 | 0.9798 |
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+ | 0.0001 | 47.0 | 5640 | 0.1932 | 0.9383 | 0.9545 | 0.9464 | 0.9796 |
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+ | 0.0 | 48.0 | 5760 | 0.1978 | 0.9340 | 0.9518 | 0.9428 | 0.9796 |
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+ | 0.0 | 49.0 | 5880 | 0.1978 | 0.9392 | 0.9545 | 0.9468 | 0.9801 |
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+ | 0.0003 | 50.0 | 6000 | 0.2032 | 0.9366 | 0.9536 | 0.9450 | 0.9798 |
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+ | 0.0 | 51.0 | 6120 | 0.2091 | 0.9367 | 0.9555 | 0.9460 | 0.9800 |
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+ | 0.0 | 52.0 | 6240 | 0.2040 | 0.9427 | 0.9564 | 0.9495 | 0.9799 |
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+ | 0.0001 | 53.0 | 6360 | 0.2029 | 0.9368 | 0.9564 | 0.9465 | 0.9810 |
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+ | 0.0001 | 54.0 | 6480 | 0.2217 | 0.9391 | 0.9527 | 0.9458 | 0.9796 |
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+ | 0.0002 | 55.0 | 6600 | 0.2129 | 0.9435 | 0.9573 | 0.9504 | 0.9800 |
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+ | 0.0 | 56.0 | 6720 | 0.2186 | 0.9443 | 0.9555 | 0.9498 | 0.9798 |
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+ | 0.0 | 57.0 | 6840 | 0.2201 | 0.9451 | 0.9555 | 0.9503 | 0.9800 |
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+ | 0.0 | 58.0 | 6960 | 0.1975 | 0.9393 | 0.9564 | 0.9477 | 0.9815 |
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+ | 0.0 | 59.0 | 7080 | 0.2077 | 0.9444 | 0.9573 | 0.9508 | 0.9810 |
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+ | 0.0001 | 60.0 | 7200 | 0.2111 | 0.9452 | 0.9564 | 0.9507 | 0.9801 |
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+ | 0.0 | 61.0 | 7320 | 0.2132 | 0.9480 | 0.9618 | 0.9549 | 0.9824 |
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+ | 0.0 | 62.0 | 7440 | 0.2058 | 0.9442 | 0.9545 | 0.9494 | 0.9808 |
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+ | 0.0023 | 63.0 | 7560 | 0.1970 | 0.9522 | 0.9591 | 0.9556 | 0.9812 |
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+ | 0.0 | 64.0 | 7680 | 0.2055 | 0.9497 | 0.9609 | 0.9553 | 0.9805 |
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+ | 0.0 | 65.0 | 7800 | 0.2050 | 0.9488 | 0.96 | 0.9544 | 0.9808 |
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+ | 0.0 | 66.0 | 7920 | 0.2336 | 0.9399 | 0.9527 | 0.9463 | 0.9778 |
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+ | 0.0 | 67.0 | 8040 | 0.1999 | 0.9447 | 0.9627 | 0.9536 | 0.9817 |
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+ | 0.0 | 68.0 | 8160 | 0.2082 | 0.9419 | 0.9582 | 0.9500 | 0.9806 |
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+ | 0.0 | 69.0 | 8280 | 0.2113 | 0.9419 | 0.9582 | 0.9500 | 0.9806 |
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+ | 0.0 | 70.0 | 8400 | 0.2164 | 0.9436 | 0.9591 | 0.9513 | 0.9803 |
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+ | 0.0 | 71.0 | 8520 | 0.2041 | 0.9411 | 0.9582 | 0.9495 | 0.9807 |
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+ | 0.0 | 72.0 | 8640 | 0.2099 | 0.9470 | 0.9582 | 0.9526 | 0.9798 |
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+ | 0.0008 | 73.0 | 8760 | 0.2107 | 0.9444 | 0.9573 | 0.9508 | 0.9798 |
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+ | 0.0 | 74.0 | 8880 | 0.2119 | 0.9470 | 0.9582 | 0.9526 | 0.9798 |
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+ | 0.0 | 75.0 | 9000 | 0.2079 | 0.9470 | 0.9582 | 0.9526 | 0.9798 |
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+ | 0.0 | 76.0 | 9120 | 0.2132 | 0.9419 | 0.9573 | 0.9495 | 0.9798 |
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+ | 0.0 | 77.0 | 9240 | 0.2163 | 0.9367 | 0.9545 | 0.9455 | 0.9797 |
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+ | 0.0 | 78.0 | 9360 | 0.2168 | 0.9384 | 0.9555 | 0.9468 | 0.9796 |
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+ | 0.0 | 79.0 | 9480 | 0.2125 | 0.9436 | 0.9582 | 0.9508 | 0.9808 |
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+ | 0.0 | 80.0 | 9600 | 0.2151 | 0.9375 | 0.9545 | 0.9459 | 0.9800 |
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+ | 0.0 | 81.0 | 9720 | 0.2150 | 0.9367 | 0.9545 | 0.9455 | 0.9799 |
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+ | 0.0 | 82.0 | 9840 | 0.2157 | 0.9368 | 0.9564 | 0.9465 | 0.9803 |
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+ | 0.0 | 83.0 | 9960 | 0.2159 | 0.9368 | 0.9564 | 0.9465 | 0.9805 |
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+ | 0.0 | 84.0 | 10080 | 0.2160 | 0.9368 | 0.9564 | 0.9465 | 0.9801 |
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+ | 0.0 | 85.0 | 10200 | 0.2164 | 0.9367 | 0.9545 | 0.9455 | 0.9799 |
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+ | 0.0 | 86.0 | 10320 | 0.2175 | 0.9384 | 0.9555 | 0.9468 | 0.9800 |
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+ | 0.0 | 87.0 | 10440 | 0.2190 | 0.9384 | 0.9555 | 0.9468 | 0.9801 |
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+ | 0.0002 | 88.0 | 10560 | 0.2193 | 0.9375 | 0.9545 | 0.9459 | 0.9801 |
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+ | 0.0 | 89.0 | 10680 | 0.2176 | 0.9383 | 0.9545 | 0.9464 | 0.9798 |
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+ | 0.0 | 90.0 | 10800 | 0.2205 | 0.9410 | 0.9573 | 0.9491 | 0.9803 |
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+ | 0.0 | 91.0 | 10920 | 0.2094 | 0.9368 | 0.9564 | 0.9465 | 0.9805 |
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+ | 0.0 | 92.0 | 11040 | 0.2094 | 0.9351 | 0.9555 | 0.9451 | 0.9804 |
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+ | 0.0 | 93.0 | 11160 | 0.2096 | 0.9376 | 0.9564 | 0.9469 | 0.9808 |
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+ | 0.0 | 94.0 | 11280 | 0.2100 | 0.9376 | 0.9564 | 0.9469 | 0.9808 |
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+ | 0.0 | 95.0 | 11400 | 0.2104 | 0.9401 | 0.9555 | 0.9477 | 0.9812 |
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+ | 0.0 | 96.0 | 11520 | 0.2107 | 0.9410 | 0.9564 | 0.9486 | 0.9814 |
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+ | 0.0 | 97.0 | 11640 | 0.2107 | 0.9401 | 0.9564 | 0.9482 | 0.9816 |
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+ | 0.0 | 98.0 | 11760 | 0.2109 | 0.9402 | 0.9582 | 0.9491 | 0.9818 |
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+ | 0.0 | 99.0 | 11880 | 0.2110 | 0.9394 | 0.9582 | 0.9487 | 0.9817 |
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+ | 0.0 | 100.0 | 12000 | 0.2110 | 0.9394 | 0.9582 | 0.9487 | 0.9817 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.46.2
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+ - Pytorch 2.4.1+cu124
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+ - Datasets 3.1.0
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+ - Tokenizers 0.20.3
config.json ADDED
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+ {
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ }
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