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swin-tiny-patch4-window7-224-finetuned-st-mean-wsdmhar-auc

Image Classification
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swin
Generated from Trainer
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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: microsoft/swin-tiny-patch4-window7-224
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: swin-tiny-patch4-window7-224-finetuned-st-mean-wsdmhar-auc
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9703856749311295
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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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+ # swin-tiny-patch4-window7-224-finetuned-st-mean-wsdmhar-auc
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+
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+ This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1076
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+ - Accuracy: 0.9704
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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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+ - 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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+ | 1.448 | 1.0 | 53 | 1.2656 | 0.5530 |
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+ | 0.7932 | 2.0 | 106 | 0.6547 | 0.7018 |
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+ | 0.5983 | 3.0 | 159 | 0.4837 | 0.8106 |
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+ | 0.4861 | 4.0 | 212 | 0.3822 | 0.8564 |
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+ | 0.4762 | 5.0 | 265 | 0.3994 | 0.8140 |
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+ | 0.4117 | 6.0 | 318 | 0.3143 | 0.8822 |
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+ | 0.3659 | 7.0 | 371 | 0.2991 | 0.8819 |
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+ | 0.355 | 8.0 | 424 | 0.3318 | 0.8688 |
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+ | 0.3146 | 9.0 | 477 | 0.2399 | 0.9101 |
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+ | 0.3243 | 10.0 | 530 | 0.2115 | 0.9260 |
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+ | 0.3233 | 11.0 | 583 | 0.2022 | 0.9322 |
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+ | 0.2736 | 12.0 | 636 | 0.1983 | 0.9256 |
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+ | 0.2765 | 13.0 | 689 | 0.1739 | 0.9411 |
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+ | 0.2191 | 14.0 | 742 | 0.1701 | 0.9421 |
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+ | 0.2416 | 15.0 | 795 | 0.2053 | 0.9208 |
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+ | 0.2039 | 16.0 | 848 | 0.1674 | 0.9401 |
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+ | 0.2248 | 17.0 | 901 | 0.1700 | 0.9394 |
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+ | 0.2331 | 18.0 | 954 | 0.1722 | 0.9439 |
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+ | 0.1889 | 19.0 | 1007 | 0.1425 | 0.9470 |
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+ | 0.1633 | 20.0 | 1060 | 0.1438 | 0.9494 |
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+ | 0.174 | 21.0 | 1113 | 0.1357 | 0.9501 |
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+ | 0.1599 | 22.0 | 1166 | 0.1346 | 0.9508 |
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+ | 0.155 | 23.0 | 1219 | 0.1318 | 0.9518 |
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+ | 0.1665 | 24.0 | 1272 | 0.1557 | 0.9477 |
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+ | 0.1519 | 25.0 | 1325 | 0.1231 | 0.9583 |
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+ | 0.143 | 26.0 | 1378 | 0.1247 | 0.9549 |
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+ | 0.1393 | 27.0 | 1431 | 0.1615 | 0.9425 |
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+ | 0.1518 | 28.0 | 1484 | 0.1246 | 0.9580 |
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+ | 0.1239 | 29.0 | 1537 | 0.1178 | 0.9614 |
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+ | 0.1297 | 30.0 | 1590 | 0.1141 | 0.9580 |
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+ | 0.165 | 31.0 | 1643 | 0.1353 | 0.9539 |
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+ | 0.1217 | 32.0 | 1696 | 0.1161 | 0.9621 |
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+ | 0.1129 | 33.0 | 1749 | 0.1152 | 0.9618 |
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+ | 0.1125 | 34.0 | 1802 | 0.1185 | 0.9621 |
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+ | 0.1083 | 35.0 | 1855 | 0.1114 | 0.9642 |
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+ | 0.1077 | 36.0 | 1908 | 0.1414 | 0.9590 |
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+ | 0.0875 | 37.0 | 1961 | 0.1360 | 0.9559 |
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+ | 0.1162 | 38.0 | 2014 | 0.1172 | 0.9618 |
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+ | 0.0925 | 39.0 | 2067 | 0.1304 | 0.9583 |
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+ | 0.109 | 40.0 | 2120 | 0.1172 | 0.9614 |
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+ | 0.1178 | 41.0 | 2173 | 0.1525 | 0.9535 |
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+ | 0.0886 | 42.0 | 2226 | 0.1616 | 0.9487 |
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+ | 0.0983 | 43.0 | 2279 | 0.1197 | 0.9590 |
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+ | 0.1209 | 44.0 | 2332 | 0.1183 | 0.9649 |
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+ | 0.0957 | 45.0 | 2385 | 0.1268 | 0.9597 |
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+ | 0.0919 | 46.0 | 2438 | 0.1143 | 0.9635 |
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+ | 0.0831 | 47.0 | 2491 | 0.1319 | 0.9601 |
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+ | 0.0888 | 48.0 | 2544 | 0.1040 | 0.9707 |
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+ | 0.0761 | 49.0 | 2597 | 0.1088 | 0.9656 |
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+ | 0.0843 | 50.0 | 2650 | 0.1046 | 0.9694 |
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+ | 0.0615 | 51.0 | 2703 | 0.0982 | 0.9652 |
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+ | 0.0705 | 52.0 | 2756 | 0.1136 | 0.9687 |
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+ | 0.0775 | 53.0 | 2809 | 0.1272 | 0.9618 |
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+ | 0.0739 | 54.0 | 2862 | 0.1185 | 0.9676 |
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+ | 0.0758 | 55.0 | 2915 | 0.1185 | 0.9649 |
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+ | 0.053 | 56.0 | 2968 | 0.1137 | 0.9663 |
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+ | 0.0675 | 57.0 | 3021 | 0.1150 | 0.9656 |
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+ | 0.0738 | 58.0 | 3074 | 0.1116 | 0.9676 |
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+ | 0.067 | 59.0 | 3127 | 0.1092 | 0.9687 |
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+ | 0.0689 | 60.0 | 3180 | 0.1116 | 0.9669 |
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+ | 0.0647 | 61.0 | 3233 | 0.1107 | 0.9656 |
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+ | 0.0707 | 62.0 | 3286 | 0.1183 | 0.9673 |
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+ | 0.0708 | 63.0 | 3339 | 0.1283 | 0.9645 |
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+ | 0.0675 | 64.0 | 3392 | 0.1222 | 0.9656 |
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+ | 0.0622 | 65.0 | 3445 | 0.1259 | 0.9669 |
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+ | 0.0541 | 66.0 | 3498 | 0.1142 | 0.9676 |
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+ | 0.0528 | 67.0 | 3551 | 0.1103 | 0.9666 |
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+ | 0.0641 | 68.0 | 3604 | 0.1363 | 0.9652 |
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+ | 0.0448 | 69.0 | 3657 | 0.1448 | 0.9652 |
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+ | 0.067 | 70.0 | 3710 | 0.1062 | 0.9687 |
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+ | 0.0674 | 71.0 | 3763 | 0.1065 | 0.9697 |
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+ | 0.0578 | 72.0 | 3816 | 0.1213 | 0.9669 |
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+ | 0.0707 | 73.0 | 3869 | 0.1115 | 0.9659 |
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+ | 0.0666 | 74.0 | 3922 | 0.1115 | 0.9707 |
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+ | 0.0361 | 75.0 | 3975 | 0.1178 | 0.9680 |
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+ | 0.047 | 76.0 | 4028 | 0.1167 | 0.9718 |
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+ | 0.0769 | 77.0 | 4081 | 0.1073 | 0.9697 |
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+ | 0.0422 | 78.0 | 4134 | 0.1116 | 0.9721 |
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+ | 0.0411 | 79.0 | 4187 | 0.1186 | 0.9676 |
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+ | 0.0402 | 80.0 | 4240 | 0.1048 | 0.9711 |
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+ | 0.0504 | 81.0 | 4293 | 0.1105 | 0.9707 |
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+ | 0.0579 | 82.0 | 4346 | 0.1007 | 0.9704 |
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+ | 0.0514 | 83.0 | 4399 | 0.1105 | 0.9711 |
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+ | 0.0398 | 84.0 | 4452 | 0.1130 | 0.9707 |
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+ | 0.0477 | 85.0 | 4505 | 0.1097 | 0.9718 |
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+ | 0.0413 | 86.0 | 4558 | 0.1091 | 0.9704 |
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+ | 0.0538 | 87.0 | 4611 | 0.1068 | 0.9718 |
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+ | 0.043 | 88.0 | 4664 | 0.1104 | 0.9725 |
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+ | 0.0434 | 89.0 | 4717 | 0.1124 | 0.9707 |
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+ | 0.0499 | 90.0 | 4770 | 0.1153 | 0.9711 |
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+ | 0.0418 | 91.0 | 4823 | 0.1121 | 0.9700 |
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+ | 0.0365 | 92.0 | 4876 | 0.1169 | 0.9711 |
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+ | 0.0493 | 93.0 | 4929 | 0.1106 | 0.9690 |
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+ | 0.0426 | 94.0 | 4982 | 0.1089 | 0.9680 |
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+ | 0.0338 | 95.0 | 5035 | 0.1096 | 0.9711 |
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+ | 0.0388 | 96.0 | 5088 | 0.1113 | 0.9694 |
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+ | 0.0404 | 97.0 | 5141 | 0.1102 | 0.9707 |
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+ | 0.0427 | 98.0 | 5194 | 0.1090 | 0.9704 |
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+ | 0.0302 | 99.0 | 5247 | 0.1076 | 0.9697 |
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+ | 0.0404 | 100.0 | 5300 | 0.1076 | 0.9704 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.5.0.dev20240829+cu118
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+ - Datasets 2.19.2
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+ - Tokenizers 0.19.1
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