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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: trainer_log
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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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+ # trainer_log
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+
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+ This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4907
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+ - Accuracy: 0.8742
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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: 32
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+ - eval_batch_size: 64
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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: 10
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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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+ | 1.047 | 0.04 | 5 | 0.9927 | 0.5753 |
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+ | 0.938 | 0.08 | 10 | 0.9320 | 0.5753 |
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+ | 0.8959 | 0.12 | 15 | 0.8764 | 0.5773 |
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+ | 0.8764 | 0.16 | 20 | 0.8308 | 0.6639 |
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+ | 0.7968 | 0.2 | 25 | 0.8045 | 0.6577 |
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+ | 0.8644 | 0.25 | 30 | 0.7779 | 0.6639 |
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+ | 0.7454 | 0.29 | 35 | 0.7561 | 0.6412 |
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+ | 0.7008 | 0.33 | 40 | 0.7157 | 0.6845 |
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+ | 0.7627 | 0.37 | 45 | 0.7027 | 0.6907 |
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+ | 0.7568 | 0.41 | 50 | 0.7270 | 0.6763 |
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+ | 0.7042 | 0.45 | 55 | 0.6770 | 0.7031 |
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+ | 0.6683 | 0.49 | 60 | 0.6364 | 0.7134 |
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+ | 0.6312 | 0.53 | 65 | 0.6151 | 0.7278 |
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+ | 0.5789 | 0.57 | 70 | 0.6003 | 0.7443 |
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+ | 0.5964 | 0.61 | 75 | 0.5665 | 0.7835 |
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+ | 0.5178 | 0.66 | 80 | 0.5506 | 0.8 |
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+ | 0.5698 | 0.7 | 85 | 0.5240 | 0.8 |
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+ | 0.5407 | 0.74 | 90 | 0.5223 | 0.7814 |
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+ | 0.6141 | 0.78 | 95 | 0.4689 | 0.8268 |
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+ | 0.4998 | 0.82 | 100 | 0.4491 | 0.8227 |
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+ | 0.4853 | 0.86 | 105 | 0.4448 | 0.8268 |
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+ | 0.4561 | 0.9 | 110 | 0.4646 | 0.8309 |
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+ | 0.5058 | 0.94 | 115 | 0.4317 | 0.8495 |
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+ | 0.4229 | 0.98 | 120 | 0.4014 | 0.8515 |
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+ | 0.2808 | 1.02 | 125 | 0.3834 | 0.8619 |
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+ | 0.3721 | 1.07 | 130 | 0.3829 | 0.8619 |
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+ | 0.3432 | 1.11 | 135 | 0.4212 | 0.8598 |
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+ | 0.3616 | 1.15 | 140 | 0.3930 | 0.8680 |
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+ | 0.3912 | 1.19 | 145 | 0.3793 | 0.8639 |
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+ | 0.4141 | 1.23 | 150 | 0.3646 | 0.8619 |
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+ | 0.2726 | 1.27 | 155 | 0.3609 | 0.8701 |
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+ | 0.2021 | 1.31 | 160 | 0.3640 | 0.8680 |
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+ | 0.3468 | 1.35 | 165 | 0.3655 | 0.8701 |
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+ | 0.2729 | 1.39 | 170 | 0.4054 | 0.8495 |
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+ | 0.3885 | 1.43 | 175 | 0.3559 | 0.8639 |
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+ | 0.446 | 1.48 | 180 | 0.3390 | 0.8680 |
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+ | 0.3337 | 1.52 | 185 | 0.3505 | 0.8660 |
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+ | 0.3507 | 1.56 | 190 | 0.3337 | 0.8804 |
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+ | 0.3864 | 1.6 | 195 | 0.3476 | 0.8660 |
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+ | 0.3495 | 1.64 | 200 | 0.3574 | 0.8577 |
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+ | 0.3388 | 1.68 | 205 | 0.3426 | 0.8701 |
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+ | 0.358 | 1.72 | 210 | 0.3439 | 0.8804 |
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+ | 0.1761 | 1.76 | 215 | 0.3461 | 0.8722 |
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+ | 0.3089 | 1.8 | 220 | 0.3638 | 0.8639 |
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+ | 0.279 | 1.84 | 225 | 0.3527 | 0.8742 |
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+ | 0.3468 | 1.89 | 230 | 0.3497 | 0.8619 |
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+ | 0.2969 | 1.93 | 235 | 0.3572 | 0.8598 |
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+ | 0.2719 | 1.97 | 240 | 0.3391 | 0.8804 |
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+ | 0.1936 | 2.01 | 245 | 0.3415 | 0.8619 |
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+ | 0.2475 | 2.05 | 250 | 0.3477 | 0.8784 |
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+ | 0.1759 | 2.09 | 255 | 0.3718 | 0.8660 |
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+ | 0.2443 | 2.13 | 260 | 0.3758 | 0.8619 |
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+ | 0.2189 | 2.17 | 265 | 0.3670 | 0.8639 |
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+ | 0.1505 | 2.21 | 270 | 0.3758 | 0.8722 |
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+ | 0.2283 | 2.25 | 275 | 0.3723 | 0.8722 |
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+ | 0.155 | 2.3 | 280 | 0.4442 | 0.8330 |
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+ | 0.317 | 2.34 | 285 | 0.3700 | 0.8701 |
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+ | 0.1566 | 2.38 | 290 | 0.4218 | 0.8619 |
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+ | 0.2294 | 2.42 | 295 | 0.3820 | 0.8660 |
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+ | 0.1567 | 2.46 | 300 | 0.3891 | 0.8660 |
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+ | 0.1875 | 2.5 | 305 | 0.3973 | 0.8722 |
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+ | 0.2741 | 2.54 | 310 | 0.4042 | 0.8742 |
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+ | 0.2363 | 2.58 | 315 | 0.3777 | 0.8660 |
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+ | 0.1964 | 2.62 | 320 | 0.3891 | 0.8639 |
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+ | 0.156 | 2.66 | 325 | 0.3998 | 0.8639 |
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+ | 0.1422 | 2.7 | 330 | 0.4022 | 0.8722 |
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+ | 0.2141 | 2.75 | 335 | 0.4239 | 0.8701 |
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+ | 0.1616 | 2.79 | 340 | 0.4094 | 0.8722 |
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+ | 0.1032 | 2.83 | 345 | 0.4263 | 0.8784 |
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+ | 0.2313 | 2.87 | 350 | 0.4579 | 0.8598 |
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+ | 0.0843 | 2.91 | 355 | 0.3989 | 0.8742 |
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+ | 0.2567 | 2.95 | 360 | 0.4051 | 0.8660 |
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+ | 0.1749 | 2.99 | 365 | 0.4136 | 0.8660 |
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+ | 0.1116 | 3.03 | 370 | 0.4312 | 0.8619 |
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+ | 0.1058 | 3.07 | 375 | 0.4007 | 0.8701 |
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+ | 0.1085 | 3.11 | 380 | 0.4174 | 0.8660 |
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+ | 0.0578 | 3.16 | 385 | 0.4163 | 0.8763 |
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+ | 0.1381 | 3.2 | 390 | 0.4578 | 0.8660 |
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+ | 0.1137 | 3.24 | 395 | 0.4259 | 0.8660 |
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+ | 0.2068 | 3.28 | 400 | 0.3976 | 0.8701 |
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+ | 0.0792 | 3.32 | 405 | 0.3824 | 0.8763 |
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+ | 0.1711 | 3.36 | 410 | 0.3793 | 0.8742 |
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+ | 0.0686 | 3.4 | 415 | 0.4013 | 0.8742 |
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+ | 0.1102 | 3.44 | 420 | 0.4113 | 0.8639 |
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+ | 0.1102 | 3.48 | 425 | 0.4276 | 0.8619 |
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+ | 0.0674 | 3.52 | 430 | 0.4222 | 0.8804 |
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+ | 0.0453 | 3.57 | 435 | 0.4326 | 0.8722 |
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+ | 0.0704 | 3.61 | 440 | 0.4684 | 0.8722 |
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+ | 0.1151 | 3.65 | 445 | 0.4640 | 0.8701 |
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+ | 0.1225 | 3.69 | 450 | 0.4408 | 0.8763 |
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+ | 0.0391 | 3.73 | 455 | 0.4520 | 0.8639 |
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+ | 0.0566 | 3.77 | 460 | 0.4558 | 0.8680 |
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+ | 0.1222 | 3.81 | 465 | 0.4599 | 0.8660 |
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+ | 0.1035 | 3.85 | 470 | 0.4630 | 0.8763 |
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+ | 0.1845 | 3.89 | 475 | 0.4796 | 0.8680 |
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+ | 0.087 | 3.93 | 480 | 0.4697 | 0.8742 |
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+ | 0.1599 | 3.98 | 485 | 0.4663 | 0.8784 |
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+ | 0.0632 | 4.02 | 490 | 0.5139 | 0.8536 |
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+ | 0.1218 | 4.06 | 495 | 0.4920 | 0.8722 |
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+ | 0.0916 | 4.1 | 500 | 0.4846 | 0.8763 |
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+ | 0.0208 | 4.14 | 505 | 0.5269 | 0.8722 |
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+ | 0.0803 | 4.18 | 510 | 0.5154 | 0.8784 |
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+ | 0.1318 | 4.22 | 515 | 0.4907 | 0.8742 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.21.1
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.4.0
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+ - Tokenizers 0.12.1