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ayubkfupm
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swin-tiny-patch4-window7-224-finetuned-st-wsdmhar-xyz

Image Classification
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swin
Generated from Trainer
Eval Results
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README.md ADDED
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+ ---
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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-wsdmhar-xyz
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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: 0.974862258953168
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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-wsdmhar-xyz
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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: 0.1062
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+ - Accuracy: 0.9749
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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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+ | 1.545 | 1.0 | 53 | 1.3735 | 0.4845 |
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+ | 0.8697 | 2.0 | 106 | 0.6895 | 0.7156 |
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+ | 0.5783 | 3.0 | 159 | 0.4415 | 0.8165 |
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+ | 0.4849 | 4.0 | 212 | 0.3737 | 0.8461 |
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+ | 0.4004 | 5.0 | 265 | 0.3442 | 0.8488 |
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+ | 0.3553 | 6.0 | 318 | 0.3271 | 0.8757 |
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+ | 0.3318 | 7.0 | 371 | 0.2491 | 0.9050 |
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+ | 0.3894 | 8.0 | 424 | 0.2636 | 0.9081 |
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+ | 0.3201 | 9.0 | 477 | 0.2368 | 0.9070 |
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+ | 0.2915 | 10.0 | 530 | 0.2390 | 0.9108 |
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+ | 0.2582 | 11.0 | 583 | 0.2044 | 0.9294 |
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+ | 0.2696 | 12.0 | 636 | 0.1948 | 0.9360 |
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+ | 0.2429 | 13.0 | 689 | 0.2282 | 0.9143 |
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+ | 0.257 | 14.0 | 742 | 0.1751 | 0.9339 |
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+ | 0.2042 | 15.0 | 795 | 0.1765 | 0.9349 |
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+ | 0.1952 | 16.0 | 848 | 0.1878 | 0.9284 |
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+ | 0.1949 | 17.0 | 901 | 0.1303 | 0.9494 |
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+ | 0.1786 | 18.0 | 954 | 0.1305 | 0.9552 |
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+ | 0.1593 | 19.0 | 1007 | 0.1249 | 0.9570 |
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+ | 0.1741 | 20.0 | 1060 | 0.1076 | 0.9601 |
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+ | 0.1638 | 21.0 | 1113 | 0.1220 | 0.9580 |
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+ | 0.1261 | 22.0 | 1166 | 0.1344 | 0.9532 |
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+ | 0.1599 | 23.0 | 1219 | 0.1293 | 0.9535 |
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+ | 0.1137 | 24.0 | 1272 | 0.1106 | 0.9621 |
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+ | 0.1257 | 25.0 | 1325 | 0.1205 | 0.9573 |
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+ | 0.1067 | 26.0 | 1378 | 0.1541 | 0.9535 |
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+ | 0.1297 | 27.0 | 1431 | 0.1128 | 0.9604 |
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+ | 0.1076 | 28.0 | 1484 | 0.1092 | 0.9594 |
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+ | 0.0917 | 29.0 | 1537 | 0.1011 | 0.9614 |
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+ | 0.0905 | 30.0 | 1590 | 0.1109 | 0.9604 |
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+ | 0.0948 | 31.0 | 1643 | 0.1046 | 0.9638 |
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+ | 0.0984 | 32.0 | 1696 | 0.1026 | 0.9669 |
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+ | 0.0921 | 33.0 | 1749 | 0.1034 | 0.9642 |
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+ | 0.0762 | 34.0 | 1802 | 0.0925 | 0.9687 |
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+ | 0.0818 | 35.0 | 1855 | 0.0966 | 0.9656 |
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+ | 0.0908 | 36.0 | 1908 | 0.0940 | 0.9687 |
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+ | 0.0699 | 37.0 | 1961 | 0.0779 | 0.9742 |
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+ | 0.0972 | 38.0 | 2014 | 0.1104 | 0.9687 |
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+ | 0.0756 | 39.0 | 2067 | 0.0838 | 0.9742 |
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+ | 0.0878 | 40.0 | 2120 | 0.1119 | 0.9673 |
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+ | 0.0819 | 41.0 | 2173 | 0.1164 | 0.9618 |
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+ | 0.0815 | 42.0 | 2226 | 0.1099 | 0.9666 |
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+ | 0.0618 | 43.0 | 2279 | 0.1003 | 0.9680 |
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+ | 0.0709 | 44.0 | 2332 | 0.0934 | 0.9721 |
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+ | 0.0697 | 45.0 | 2385 | 0.0869 | 0.9731 |
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+ | 0.0551 | 46.0 | 2438 | 0.1086 | 0.9694 |
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+ | 0.049 | 47.0 | 2491 | 0.1036 | 0.9687 |
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+ | 0.0646 | 48.0 | 2544 | 0.0854 | 0.9735 |
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+ | 0.0704 | 49.0 | 2597 | 0.0959 | 0.9714 |
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+ | 0.0578 | 50.0 | 2650 | 0.1034 | 0.9707 |
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+ | 0.0579 | 51.0 | 2703 | 0.0965 | 0.9700 |
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+ | 0.051 | 52.0 | 2756 | 0.0962 | 0.9721 |
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+ | 0.0477 | 53.0 | 2809 | 0.1218 | 0.9690 |
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+ | 0.0769 | 54.0 | 2862 | 0.1027 | 0.9714 |
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+ | 0.0493 | 55.0 | 2915 | 0.1175 | 0.9725 |
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+ | 0.0535 | 56.0 | 2968 | 0.1140 | 0.9690 |
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+ | 0.0359 | 57.0 | 3021 | 0.0990 | 0.9725 |
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+ | 0.0388 | 58.0 | 3074 | 0.0965 | 0.9700 |
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+ | 0.0455 | 59.0 | 3127 | 0.1119 | 0.9700 |
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+ | 0.0584 | 60.0 | 3180 | 0.0989 | 0.9735 |
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+ | 0.0555 | 61.0 | 3233 | 0.1130 | 0.9680 |
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+ | 0.0567 | 62.0 | 3286 | 0.1045 | 0.9721 |
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+ | 0.0543 | 63.0 | 3339 | 0.1168 | 0.9707 |
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+ | 0.0562 | 64.0 | 3392 | 0.1196 | 0.9649 |
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+ | 0.0472 | 65.0 | 3445 | 0.1034 | 0.9725 |
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+ | 0.0387 | 66.0 | 3498 | 0.1125 | 0.9728 |
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+ | 0.0485 | 67.0 | 3551 | 0.1057 | 0.9738 |
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+ | 0.0395 | 68.0 | 3604 | 0.1252 | 0.9725 |
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+ | 0.0266 | 69.0 | 3657 | 0.1023 | 0.9742 |
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+ | 0.0409 | 70.0 | 3710 | 0.1095 | 0.9738 |
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+ | 0.0349 | 71.0 | 3763 | 0.1101 | 0.9752 |
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+ | 0.0205 | 72.0 | 3816 | 0.1127 | 0.9725 |
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+ | 0.0336 | 73.0 | 3869 | 0.1131 | 0.9735 |
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+ | 0.0305 | 74.0 | 3922 | 0.0987 | 0.9749 |
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+ | 0.0298 | 75.0 | 3975 | 0.1051 | 0.9742 |
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+ | 0.0304 | 76.0 | 4028 | 0.1049 | 0.9728 |
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+ | 0.051 | 77.0 | 4081 | 0.1134 | 0.9711 |
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+ | 0.045 | 78.0 | 4134 | 0.1334 | 0.9707 |
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+ | 0.0345 | 79.0 | 4187 | 0.1233 | 0.9707 |
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+ | 0.0328 | 80.0 | 4240 | 0.1106 | 0.9728 |
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+ | 0.0391 | 81.0 | 4293 | 0.1073 | 0.9735 |
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+ | 0.0383 | 82.0 | 4346 | 0.1189 | 0.9707 |
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+ | 0.0299 | 83.0 | 4399 | 0.1131 | 0.9756 |
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+ | 0.0195 | 84.0 | 4452 | 0.1267 | 0.9714 |
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+ | 0.0181 | 85.0 | 4505 | 0.1200 | 0.9700 |
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+ | 0.0266 | 86.0 | 4558 | 0.1086 | 0.9752 |
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+ | 0.0322 | 87.0 | 4611 | 0.1149 | 0.9735 |
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+ | 0.0325 | 88.0 | 4664 | 0.1130 | 0.9738 |
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+ | 0.0303 | 89.0 | 4717 | 0.1105 | 0.9749 |
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+ | 0.0275 | 90.0 | 4770 | 0.1078 | 0.9752 |
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+ | 0.0281 | 91.0 | 4823 | 0.1077 | 0.9742 |
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+ | 0.0231 | 92.0 | 4876 | 0.1060 | 0.9752 |
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+ | 0.022 | 93.0 | 4929 | 0.1077 | 0.9749 |
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+ | 0.0219 | 94.0 | 4982 | 0.1080 | 0.9749 |
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+ | 0.0184 | 95.0 | 5035 | 0.1061 | 0.9756 |
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+ | 0.0198 | 96.0 | 5088 | 0.1047 | 0.9749 |
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+ | 0.0355 | 97.0 | 5141 | 0.1084 | 0.9735 |
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+ | 0.0309 | 98.0 | 5194 | 0.1088 | 0.9735 |
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+ | 0.0324 | 99.0 | 5247 | 0.1066 | 0.9742 |
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+ | 0.0216 | 100.0 | 5300 | 0.1062 | 0.9749 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.43.2
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+ - Pytorch 2.3.1+cu118
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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