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finetuned-AffectNet

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beit
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  2. model.safetensors +1 -1
  3. runs/Jan05_11-00-45_2247cd98422c/events.out.tfevents.1704452460.2247cd98422c.4324.0 +2 -2
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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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: finetuned-AffectNet
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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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+ # finetuned-AffectNet
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8122
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+ - Accuracy: 0.7345
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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-06
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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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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ - lr_scheduler_warmup_ratio: 0.1
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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 | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 2.0686 | 1.0 | 163 | 2.0963 | 0.1549 |
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+ | 1.7148 | 2.0 | 327 | 1.7250 | 0.2943 |
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+ | 1.4591 | 3.0 | 490 | 1.4418 | 0.4204 |
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+ | 1.3351 | 4.0 | 654 | 1.2648 | 0.5194 |
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+ | 1.1343 | 5.0 | 817 | 1.0728 | 0.5908 |
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+ | 1.1022 | 6.0 | 981 | 0.9741 | 0.6355 |
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+ | 1.0476 | 7.0 | 1144 | 0.9203 | 0.6631 |
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+ | 1.0049 | 8.0 | 1308 | 0.8769 | 0.6760 |
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+ | 0.9561 | 9.0 | 1471 | 0.8438 | 0.6966 |
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+ | 0.9409 | 10.0 | 1635 | 0.8283 | 0.6988 |
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+ | 0.9419 | 11.0 | 1798 | 0.7867 | 0.7164 |
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+ | 0.89 | 12.0 | 1962 | 0.7858 | 0.7139 |
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+ | 0.8761 | 13.0 | 2125 | 0.7704 | 0.7147 |
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+ | 0.8662 | 14.0 | 2289 | 0.7590 | 0.7225 |
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+ | 0.8561 | 15.0 | 2452 | 0.7574 | 0.7199 |
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+ | 0.8234 | 16.0 | 2616 | 0.7457 | 0.7238 |
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+ | 0.844 | 17.0 | 2779 | 0.7416 | 0.7255 |
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+ | 0.7908 | 18.0 | 2943 | 0.7485 | 0.7255 |
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+ | 0.809 | 19.0 | 3106 | 0.7428 | 0.7250 |
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+ | 0.7976 | 20.0 | 3270 | 0.7597 | 0.7203 |
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+ | 0.7691 | 21.0 | 3433 | 0.7333 | 0.7345 |
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+ | 0.7408 | 22.0 | 3597 | 0.7362 | 0.7246 |
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+ | 0.7516 | 23.0 | 3760 | 0.7301 | 0.7298 |
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+ | 0.7887 | 24.0 | 3924 | 0.7263 | 0.7332 |
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+ | 0.7475 | 25.0 | 4087 | 0.7301 | 0.7293 |
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+ | 0.7619 | 26.0 | 4251 | 0.7334 | 0.7298 |
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+ | 0.7509 | 27.0 | 4414 | 0.7332 | 0.7345 |
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+ | 0.7212 | 28.0 | 4578 | 0.7301 | 0.7367 |
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+ | 0.7053 | 29.0 | 4741 | 0.7293 | 0.7328 |
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+ | 0.6634 | 30.0 | 4905 | 0.7412 | 0.7298 |
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+ | 0.677 | 31.0 | 5068 | 0.7221 | 0.7375 |
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+ | 0.6453 | 32.0 | 5232 | 0.7281 | 0.7392 |
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+ | 0.6961 | 33.0 | 5395 | 0.7280 | 0.7392 |
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+ | 0.7135 | 34.0 | 5559 | 0.7348 | 0.7362 |
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+ | 0.6871 | 35.0 | 5722 | 0.7334 | 0.7293 |
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+ | 0.6829 | 36.0 | 5886 | 0.7281 | 0.7328 |
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+ | 0.6742 | 37.0 | 6049 | 0.7332 | 0.7354 |
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+ | 0.6167 | 38.0 | 6213 | 0.7274 | 0.7384 |
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+ | 0.665 | 39.0 | 6376 | 0.7322 | 0.7311 |
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+ | 0.6433 | 40.0 | 6540 | 0.7473 | 0.7345 |
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+ | 0.6661 | 41.0 | 6703 | 0.7358 | 0.7341 |
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+ | 0.6424 | 42.0 | 6867 | 0.7413 | 0.7324 |
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+ | 0.6369 | 43.0 | 7030 | 0.7314 | 0.7414 |
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+ | 0.611 | 44.0 | 7194 | 0.7325 | 0.7388 |
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+ | 0.6556 | 45.0 | 7357 | 0.7485 | 0.7354 |
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+ | 0.6524 | 46.0 | 7521 | 0.7434 | 0.7418 |
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+ | 0.6176 | 47.0 | 7684 | 0.7402 | 0.7410 |
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+ | 0.6142 | 48.0 | 7848 | 0.7480 | 0.7315 |
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+ | 0.5968 | 49.0 | 8011 | 0.7457 | 0.7384 |
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+ | 0.6132 | 50.0 | 8175 | 0.7514 | 0.7328 |
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+ | 0.592 | 51.0 | 8338 | 0.7500 | 0.7375 |
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+ | 0.6347 | 52.0 | 8502 | 0.7533 | 0.7345 |
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+ | 0.5976 | 53.0 | 8665 | 0.7539 | 0.7324 |
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+ | 0.5496 | 54.0 | 8829 | 0.7495 | 0.7388 |
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+ | 0.5845 | 55.0 | 8992 | 0.7550 | 0.7367 |
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+ | 0.5624 | 56.0 | 9156 | 0.7606 | 0.7362 |
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+ | 0.5582 | 57.0 | 9319 | 0.7598 | 0.7341 |
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+ | 0.6206 | 58.0 | 9483 | 0.7608 | 0.7345 |
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+ | 0.5647 | 59.0 | 9646 | 0.7578 | 0.7388 |
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+ | 0.6093 | 60.0 | 9810 | 0.7646 | 0.7358 |
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+ | 0.5625 | 61.0 | 9973 | 0.7622 | 0.7388 |
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+ | 0.6114 | 62.0 | 10137 | 0.7702 | 0.7324 |
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+ | 0.5304 | 63.0 | 10300 | 0.7710 | 0.7367 |
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+ | 0.5646 | 64.0 | 10464 | 0.7807 | 0.7298 |
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+ | 0.5774 | 65.0 | 10627 | 0.7793 | 0.7328 |
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+ | 0.5825 | 66.0 | 10791 | 0.7786 | 0.7375 |
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+ | 0.5111 | 67.0 | 10954 | 0.7742 | 0.7380 |
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+ | 0.5849 | 68.0 | 11118 | 0.7779 | 0.7349 |
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+ | 0.5454 | 69.0 | 11281 | 0.7795 | 0.7367 |
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+ | 0.5158 | 70.0 | 11445 | 0.7806 | 0.7345 |
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+ | 0.5576 | 71.0 | 11608 | 0.7903 | 0.7345 |
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+ | 0.5394 | 72.0 | 11772 | 0.7812 | 0.7380 |
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+ | 0.5099 | 73.0 | 11935 | 0.7808 | 0.7354 |
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+ | 0.5209 | 74.0 | 12099 | 0.7851 | 0.7319 |
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+ | 0.5322 | 75.0 | 12262 | 0.7908 | 0.7401 |
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+ | 0.5351 | 76.0 | 12426 | 0.7960 | 0.7306 |
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+ | 0.5272 | 77.0 | 12589 | 0.7924 | 0.7324 |
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+ | 0.477 | 78.0 | 12753 | 0.7981 | 0.7332 |
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+ | 0.5186 | 79.0 | 12916 | 0.7942 | 0.7341 |
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+ | 0.5366 | 80.0 | 13080 | 0.8016 | 0.7367 |
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+ | 0.4809 | 81.0 | 13243 | 0.8014 | 0.7341 |
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+ | 0.4889 | 82.0 | 13407 | 0.8008 | 0.7354 |
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+ | 0.5287 | 83.0 | 13570 | 0.8010 | 0.7349 |
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+ | 0.4926 | 84.0 | 13734 | 0.8047 | 0.7371 |
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+ | 0.4989 | 85.0 | 13897 | 0.8046 | 0.7384 |
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+ | 0.5483 | 86.0 | 14061 | 0.8022 | 0.7371 |
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+ | 0.5157 | 87.0 | 14224 | 0.8055 | 0.7358 |
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+ | 0.4999 | 88.0 | 14388 | 0.8071 | 0.7319 |
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+ | 0.519 | 89.0 | 14551 | 0.8083 | 0.7362 |
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+ | 0.4534 | 90.0 | 14715 | 0.8082 | 0.7384 |
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+ | 0.429 | 91.0 | 14878 | 0.8103 | 0.7354 |
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+ | 0.5073 | 92.0 | 15042 | 0.8116 | 0.7336 |
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+ | 0.5358 | 93.0 | 15205 | 0.8106 | 0.7341 |
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+ | 0.5049 | 94.0 | 15369 | 0.8111 | 0.7315 |
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+ | 0.4745 | 95.0 | 15532 | 0.8118 | 0.7336 |
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+ | 0.5052 | 96.0 | 15696 | 0.8104 | 0.7371 |
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+ | 0.495 | 97.0 | 15859 | 0.8101 | 0.7354 |
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+ | 0.4752 | 98.0 | 16023 | 0.8117 | 0.7349 |
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+ | 0.4927 | 99.0 | 16186 | 0.8120 | 0.7336 |
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+ | 0.4875 | 99.69 | 16300 | 0.8122 | 0.7345 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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