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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: google/vit-base-patch16-224-in21k
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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: model_dir
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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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+ # model_dir
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1045
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+ - Accuracy: 0.9799
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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: 0.0002
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+ - train_batch_size: 1
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+ - eval_batch_size: 8
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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: 4
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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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+ | 0.8814 | 0.0203 | 100 | 0.9432 | 0.7601 |
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+ | 0.4374 | 0.0405 | 200 | 0.4927 | 0.8864 |
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+ | 0.0042 | 0.0608 | 300 | 0.3534 | 0.9267 |
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+ | 0.0093 | 0.0811 | 400 | 0.2335 | 0.9414 |
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+ | 0.125 | 0.1013 | 500 | 0.3630 | 0.9286 |
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+ | 0.4924 | 0.1216 | 600 | 0.2374 | 0.9469 |
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+ | 0.0052 | 0.1419 | 700 | 0.2015 | 0.9487 |
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+ | 0.3738 | 0.1621 | 800 | 0.4200 | 0.8864 |
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+ | 0.4533 | 0.1824 | 900 | 0.2573 | 0.9286 |
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+ | 0.027 | 0.2027 | 1000 | 0.3408 | 0.9121 |
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+ | 0.6685 | 0.2229 | 1100 | 0.3140 | 0.8260 |
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+ | 0.0703 | 0.2432 | 1200 | 0.2425 | 0.9322 |
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+ | 0.9411 | 0.2635 | 1300 | 0.7809 | 0.8223 |
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+ | 0.4378 | 0.2837 | 1400 | 0.6968 | 0.8223 |
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+ | 0.7127 | 0.3040 | 1500 | 0.3294 | 0.8242 |
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+ | 0.9465 | 0.3243 | 1600 | 0.4913 | 0.8223 |
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+ | 0.3834 | 0.3445 | 1700 | 0.2594 | 0.9048 |
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+ | 0.6691 | 0.3648 | 1800 | 0.3537 | 0.8993 |
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+ | 0.3002 | 0.3851 | 1900 | 0.2502 | 0.9286 |
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+ | 0.0473 | 0.4054 | 2000 | 0.2312 | 0.9322 |
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+ | 0.634 | 0.4256 | 2100 | 0.2406 | 0.9359 |
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+ | 0.4471 | 0.4459 | 2200 | 0.2983 | 0.9377 |
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+ | 0.3229 | 0.4662 | 2300 | 0.3601 | 0.9212 |
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+ | 0.4769 | 0.4864 | 2400 | 0.2990 | 0.9011 |
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+ | 0.0135 | 0.5067 | 2500 | 0.3134 | 0.9029 |
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+ | 0.3025 | 0.5270 | 2600 | 0.1748 | 0.9505 |
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+ | 0.0114 | 0.5472 | 2700 | 0.2898 | 0.9212 |
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+ | 0.1636 | 0.5675 | 2800 | 0.2281 | 0.9396 |
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+ | 0.7427 | 0.5878 | 2900 | 0.2334 | 0.9341 |
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+ | 0.0083 | 0.6080 | 3000 | 0.2466 | 0.9359 |
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+ | 0.0041 | 0.6283 | 3100 | 0.2737 | 0.9432 |
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+ | 1.7268 | 0.6486 | 3200 | 0.2626 | 0.9396 |
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+ | 0.0115 | 0.6688 | 3300 | 0.2621 | 0.9304 |
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+ | 0.6196 | 0.6891 | 3400 | 0.3546 | 0.9267 |
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+ | 0.0141 | 0.7094 | 3500 | 0.2064 | 0.9505 |
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+ | 0.006 | 0.7296 | 3600 | 0.2204 | 0.9487 |
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+ | 0.0226 | 0.7499 | 3700 | 0.2544 | 0.9451 |
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+ | 0.0084 | 0.7702 | 3800 | 0.1698 | 0.9542 |
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+ | 0.0035 | 0.7904 | 3900 | 0.2541 | 0.9304 |
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+ | 0.0137 | 0.8107 | 4000 | 0.1235 | 0.9670 |
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+ | 0.9026 | 0.8310 | 4100 | 0.3319 | 0.9249 |
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+ | 0.4531 | 0.8512 | 4200 | 0.2221 | 0.9414 |
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+ | 0.0039 | 0.8715 | 4300 | 0.1823 | 0.9560 |
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+ | 1.3298 | 0.8918 | 4400 | 0.2125 | 0.9542 |
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+ | 0.4403 | 0.9120 | 4500 | 0.4900 | 0.8938 |
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+ | 0.0025 | 0.9323 | 4600 | 0.3010 | 0.9249 |
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+ | 0.0056 | 0.9526 | 4700 | 0.2978 | 0.9267 |
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+ | 0.3642 | 0.9728 | 4800 | 0.2162 | 0.9451 |
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+ | 0.5704 | 0.9931 | 4900 | 0.2459 | 0.9414 |
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+ | 0.1761 | 1.0134 | 5000 | 0.1674 | 0.9652 |
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+ | 0.0023 | 1.0336 | 5100 | 0.1855 | 0.9542 |
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+ | 0.1477 | 1.0539 | 5200 | 0.1516 | 0.9652 |
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+ | 0.0034 | 1.0742 | 5300 | 0.8117 | 0.7326 |
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+ | 0.4936 | 1.0944 | 5400 | 0.2102 | 0.9377 |
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+ | 0.0158 | 1.1147 | 5500 | 0.1886 | 0.9524 |
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+ | 0.0041 | 1.1350 | 5600 | 0.2544 | 0.9286 |
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+ | 0.7993 | 1.1552 | 5700 | 0.2523 | 0.9304 |
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+ | 0.6292 | 1.1755 | 5800 | 0.1681 | 0.9451 |
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+ | 0.0048 | 1.1958 | 5900 | 0.2746 | 0.9377 |
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+ | 0.4908 | 1.2161 | 6000 | 0.3194 | 0.9359 |
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+ | 0.4156 | 1.2363 | 6100 | 0.1320 | 0.9744 |
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+ | 0.0056 | 1.2566 | 6200 | 0.3195 | 0.8993 |
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+ | 0.0013 | 1.2769 | 6300 | 0.1581 | 0.9615 |
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+ | 0.0027 | 1.2971 | 6400 | 0.2660 | 0.9414 |
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+ | 0.1753 | 1.3174 | 6500 | 0.1858 | 0.9560 |
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+ | 0.0013 | 1.3377 | 6600 | 0.2018 | 0.9615 |
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+ | 0.0033 | 1.3579 | 6700 | 0.1475 | 0.9707 |
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+ | 0.0037 | 1.3782 | 6800 | 0.1417 | 0.9689 |
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+ | 1.2775 | 1.3985 | 6900 | 0.1101 | 0.9670 |
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+ | 0.0051 | 1.4187 | 7000 | 0.1292 | 0.9707 |
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+ | 0.4954 | 1.4390 | 7100 | 0.2473 | 0.9469 |
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+ | 0.1533 | 1.4593 | 7200 | 0.1181 | 0.9707 |
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+ | 0.0022 | 1.4795 | 7300 | 0.1512 | 0.9707 |
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+ | 0.005 | 1.4998 | 7400 | 0.1329 | 0.9670 |
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+ | 0.4396 | 1.5201 | 7500 | 0.1219 | 0.9725 |
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+ | 0.0044 | 1.5403 | 7600 | 0.1665 | 0.9670 |
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+ | 0.7054 | 1.5606 | 7700 | 0.1652 | 0.9670 |
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+ | 0.4057 | 1.5809 | 7800 | 0.1683 | 0.9542 |
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+ | 0.011 | 1.6011 | 7900 | 0.3927 | 0.9286 |
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+ | 0.7 | 1.6214 | 8000 | 0.0999 | 0.9762 |
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+ | 0.0026 | 1.6417 | 8100 | 0.1249 | 0.9744 |
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+ | 0.002 | 1.6619 | 8200 | 0.1386 | 0.9615 |
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+ | 0.0041 | 1.6822 | 8300 | 0.1175 | 0.9670 |
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+ | 0.0034 | 1.7025 | 8400 | 0.1160 | 0.9725 |
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+ | 0.0041 | 1.7227 | 8500 | 0.2097 | 0.9542 |
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+ | 0.3303 | 1.7430 | 8600 | 0.1527 | 0.9597 |
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+ | 0.006 | 1.7633 | 8700 | 0.1389 | 0.9670 |
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+ | 0.0012 | 1.7835 | 8800 | 0.1799 | 0.9597 |
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+ | 0.0027 | 1.8038 | 8900 | 0.1717 | 0.9615 |
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+ | 0.4926 | 1.8241 | 9000 | 0.1517 | 0.9670 |
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+ | 0.0023 | 1.8443 | 9100 | 0.1272 | 0.9744 |
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+ | 0.5028 | 1.8646 | 9200 | 0.1444 | 0.9725 |
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+ | 0.0051 | 1.8849 | 9300 | 0.1276 | 0.9744 |
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+ | 0.0019 | 1.9051 | 9400 | 0.1550 | 0.9689 |
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+ | 0.0052 | 1.9254 | 9500 | 0.1958 | 0.9634 |
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+ | 0.0099 | 1.9457 | 9600 | 0.1359 | 0.9689 |
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+ | 0.3494 | 1.9660 | 9700 | 0.1969 | 0.9542 |
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+ | 0.0035 | 1.9862 | 9800 | 0.1671 | 0.9579 |
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+ | 0.0025 | 2.0065 | 9900 | 0.1435 | 0.9707 |
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+ | 0.0006 | 2.0268 | 10000 | 0.1187 | 0.9799 |
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+ | 0.0035 | 2.0470 | 10100 | 0.1303 | 0.9780 |
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+ | 0.7492 | 2.0673 | 10200 | 0.1294 | 0.9762 |
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+ | 0.0154 | 2.0876 | 10300 | 0.1108 | 0.9762 |
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+ | 0.0007 | 2.1078 | 10400 | 0.2675 | 0.9487 |
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+ | 0.0008 | 2.1281 | 10500 | 0.1334 | 0.9689 |
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+ | 0.003 | 2.1484 | 10600 | 0.1583 | 0.9670 |
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+ | 0.4043 | 2.1686 | 10700 | 0.1198 | 0.9780 |
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+ | 0.0016 | 2.1889 | 10800 | 0.1130 | 0.9799 |
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+ | 0.0033 | 2.2092 | 10900 | 0.1102 | 0.9762 |
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+ | 1.0287 | 2.2294 | 11000 | 0.1053 | 0.9762 |
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+ | 0.3159 | 2.2497 | 11100 | 0.1004 | 0.9780 |
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+ | 0.0464 | 2.2700 | 11200 | 0.1181 | 0.9762 |
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+ | 0.002 | 2.2902 | 11300 | 0.2652 | 0.9560 |
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+ | 0.0758 | 2.3105 | 11400 | 0.1413 | 0.9725 |
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+ | 0.0027 | 2.3308 | 11500 | 0.2025 | 0.9451 |
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+ | 0.0011 | 2.3510 | 11600 | 0.1372 | 0.9725 |
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+ | 0.0009 | 2.3713 | 11700 | 0.1458 | 0.9725 |
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+ | 0.4178 | 2.3916 | 11800 | 0.1403 | 0.9725 |
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+ | 0.0028 | 2.4118 | 11900 | 0.1406 | 0.9725 |
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+ | 0.0009 | 2.4321 | 12000 | 0.1295 | 0.9725 |
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+ | 0.002 | 2.4524 | 12100 | 0.1685 | 0.9670 |
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+ | 0.0022 | 2.4726 | 12200 | 0.1151 | 0.9744 |
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+ | 0.0008 | 2.4929 | 12300 | 0.1635 | 0.9689 |
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+ | 0.0035 | 2.5132 | 12400 | 0.1283 | 0.9744 |
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+ | 0.7689 | 2.5334 | 12500 | 0.1551 | 0.9689 |
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+ | 0.0126 | 2.5537 | 12600 | 0.1144 | 0.9762 |
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+ | 0.0028 | 2.5740 | 12700 | 0.0919 | 0.9835 |
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+ | 0.0053 | 2.5942 | 12800 | 0.1132 | 0.9762 |
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+ | 0.0018 | 2.6145 | 12900 | 0.0851 | 0.9853 |
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+ | 0.0014 | 2.6348 | 13000 | 0.1095 | 0.9780 |
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+ | 0.0017 | 2.6550 | 13100 | 0.0878 | 0.9817 |
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+ | 0.0014 | 2.6753 | 13200 | 0.1322 | 0.9762 |
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+ | 0.0015 | 2.6956 | 13300 | 0.1059 | 0.9799 |
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+ | 0.0036 | 2.7158 | 13400 | 0.0927 | 0.9817 |
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+ | 0.0051 | 2.7361 | 13500 | 0.1009 | 0.9799 |
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+ | 0.0028 | 2.7564 | 13600 | 0.1680 | 0.9670 |
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+ | 0.6951 | 2.7767 | 13700 | 0.2497 | 0.9487 |
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+ | 0.0096 | 2.7969 | 13800 | 0.1138 | 0.9780 |
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+ | 0.5063 | 2.8172 | 13900 | 0.1151 | 0.9744 |
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+ | 0.0026 | 2.8375 | 14000 | 0.1179 | 0.9762 |
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+ | 0.0041 | 2.8577 | 14100 | 0.1266 | 0.9744 |
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+ | 0.0019 | 2.8780 | 14200 | 0.0998 | 0.9780 |
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+ | 0.0038 | 2.8983 | 14300 | 0.1290 | 0.9652 |
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+ | 0.0131 | 2.9185 | 14400 | 0.1998 | 0.9414 |
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+ | 0.0037 | 2.9388 | 14500 | 0.1214 | 0.9634 |
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+ | 0.2382 | 2.9591 | 14600 | 0.1097 | 0.9780 |
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+ | 0.0021 | 2.9793 | 14700 | 0.1152 | 0.9780 |
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+ | 0.002 | 2.9996 | 14800 | 0.1001 | 0.9799 |
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+ | 0.0027 | 3.0199 | 14900 | 0.1291 | 0.9780 |
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+ | 0.971 | 3.0401 | 15000 | 0.1617 | 0.9689 |
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+ | 0.0024 | 3.0604 | 15100 | 0.1245 | 0.9707 |
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+ | 0.0172 | 3.0807 | 15200 | 0.1246 | 0.9725 |
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+ | 0.0016 | 3.1009 | 15300 | 0.1628 | 0.9634 |
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+ | 0.0016 | 3.1212 | 15400 | 0.1621 | 0.9634 |
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+ | 0.0005 | 3.1415 | 15500 | 0.1104 | 0.9762 |
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+ | 0.3195 | 3.1617 | 15600 | 0.1447 | 0.9725 |
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+ | 2.3502 | 3.1820 | 15700 | 0.1827 | 0.9652 |
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+ | 0.4252 | 3.2023 | 15800 | 0.1077 | 0.9762 |
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+ | 0.0042 | 3.2225 | 15900 | 0.1431 | 0.9707 |
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+ | 1.0207 | 3.2428 | 16000 | 0.1287 | 0.9744 |
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+ | 0.5064 | 3.2631 | 16100 | 0.1663 | 0.9689 |
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+ | 0.0018 | 3.2833 | 16200 | 0.1327 | 0.9725 |
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+ | 0.0006 | 3.3036 | 16300 | 0.1163 | 0.9762 |
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+ | 0.0039 | 3.3239 | 16400 | 0.1413 | 0.9725 |
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+ | 0.5045 | 3.3441 | 16500 | 0.1572 | 0.9689 |
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+ | 0.0069 | 3.3644 | 16600 | 0.1553 | 0.9670 |
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+ | 0.0058 | 3.3847 | 16700 | 0.1022 | 0.9780 |
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+ | 0.006 | 3.4049 | 16800 | 0.0993 | 0.9780 |
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+ | 0.002 | 3.4252 | 16900 | 0.0954 | 0.9799 |
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+ | 0.0082 | 3.4455 | 17000 | 0.0976 | 0.9762 |
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+ | 0.0029 | 3.4657 | 17100 | 0.0978 | 0.9780 |
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+ | 0.0008 | 3.4860 | 17200 | 0.0973 | 0.9799 |
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+ | 0.0014 | 3.5063 | 17300 | 0.0979 | 0.9799 |
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+ | 0.0008 | 3.5266 | 17400 | 0.1151 | 0.9744 |
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+ | 0.0023 | 3.5468 | 17500 | 0.1093 | 0.9780 |
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+ | 0.0012 | 3.5671 | 17600 | 0.0996 | 0.9799 |
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+ | 0.0016 | 3.5874 | 17700 | 0.0980 | 0.9817 |
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+ | 0.0015 | 3.6076 | 17800 | 0.1052 | 0.9799 |
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+ | 0.0018 | 3.6279 | 17900 | 0.1054 | 0.9799 |
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+ | 0.003 | 3.6482 | 18000 | 0.1052 | 0.9780 |
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+ | 0.002 | 3.6684 | 18100 | 0.1063 | 0.9799 |
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+ | 0.0011 | 3.6887 | 18200 | 0.1195 | 0.9762 |
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+ | 0.4766 | 3.7090 | 18300 | 0.0873 | 0.9835 |
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+ | 0.0026 | 3.7292 | 18400 | 0.0876 | 0.9835 |
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+ | 0.0006 | 3.7495 | 18500 | 0.0942 | 0.9835 |
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+ | 0.0014 | 3.7698 | 18600 | 0.0944 | 0.9835 |
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+ | 0.0013 | 3.7900 | 18700 | 0.0972 | 0.9817 |
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+ | 0.0016 | 3.8103 | 18800 | 0.1044 | 0.9817 |
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+ | 0.0009 | 3.8306 | 18900 | 0.1039 | 0.9799 |
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+ | 0.0008 | 3.8508 | 19000 | 0.0976 | 0.9817 |
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+ | 0.0005 | 3.8711 | 19100 | 0.0969 | 0.9835 |
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+ | 0.0009 | 3.8914 | 19200 | 0.0964 | 0.9835 |
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+ | 0.0005 | 3.9116 | 19300 | 0.1020 | 0.9799 |
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+ | 0.5488 | 3.9319 | 19400 | 0.0986 | 0.9817 |
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+ | 0.0014 | 3.9522 | 19500 | 0.0963 | 0.9835 |
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+ | 0.001 | 3.9724 | 19600 | 0.1037 | 0.9799 |
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+ | 0.0009 | 3.9927 | 19700 | 0.1045 | 0.9799 |
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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 2.5.1+cpu
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+ - Datasets 2.11.0
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+ - Tokenizers 0.20.3
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