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swinv2-tiny-patch4-window8-256-dmae-humeda-DAV67

Image Classification
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swinv2
Generated from Trainer
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  2. model.safetensors +1 -1
  3. runs/Mar21_01-57-17_721b7bb2497f/events.out.tfevents.1742522266.721b7bb2497f.1961.0 +2 -2
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/swinv2-tiny-patch4-window8-256
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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: swinv2-tiny-patch4-window8-256-dmae-humeda-DAV67
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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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+ # swinv2-tiny-patch4-window8-256-dmae-humeda-DAV67
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+
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+ This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3766
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+ - Accuracy: 0.8914
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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: 4e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 45
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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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+ | 1.103 | 1.0 | 18 | 1.0588 | 0.4 |
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+ | 0.9007 | 2.0 | 36 | 0.5651 | 0.8229 |
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+ | 0.497 | 3.0 | 54 | 0.3559 | 0.8743 |
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+ | 0.4178 | 4.0 | 72 | 0.4171 | 0.7886 |
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+ | 0.4303 | 5.0 | 90 | 0.6884 | 0.7314 |
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+ | 0.485 | 6.0 | 108 | 0.3255 | 0.8629 |
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+ | 0.3345 | 7.0 | 126 | 0.2631 | 0.9029 |
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+ | 0.3058 | 8.0 | 144 | 0.3533 | 0.8343 |
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+ | 0.35 | 9.0 | 162 | 0.2853 | 0.8686 |
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+ | 0.2535 | 10.0 | 180 | 0.2529 | 0.9143 |
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+ | 0.21 | 11.0 | 198 | 0.3806 | 0.84 |
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+ | 0.2414 | 12.0 | 216 | 0.2829 | 0.92 |
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+ | 0.1978 | 13.0 | 234 | 0.3011 | 0.9143 |
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+ | 0.1683 | 14.0 | 252 | 0.2486 | 0.9086 |
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+ | 0.2351 | 15.0 | 270 | 0.3612 | 0.8629 |
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+ | 0.264 | 16.0 | 288 | 0.3643 | 0.88 |
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+ | 0.1714 | 17.0 | 306 | 0.2481 | 0.9086 |
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+ | 0.1714 | 18.0 | 324 | 0.3479 | 0.8914 |
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+ | 0.1886 | 19.0 | 342 | 0.2644 | 0.9029 |
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+ | 0.1522 | 20.0 | 360 | 0.2587 | 0.8971 |
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+ | 0.1468 | 21.0 | 378 | 0.2832 | 0.9029 |
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+ | 0.1364 | 22.0 | 396 | 0.2830 | 0.9029 |
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+ | 0.1294 | 23.0 | 414 | 0.2954 | 0.8914 |
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+ | 0.122 | 24.0 | 432 | 0.3801 | 0.8743 |
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+ | 0.1114 | 25.0 | 450 | 0.3375 | 0.9029 |
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+ | 0.12 | 26.0 | 468 | 0.3696 | 0.8743 |
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+ | 0.121 | 27.0 | 486 | 0.3460 | 0.8857 |
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+ | 0.1056 | 28.0 | 504 | 0.3296 | 0.9029 |
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+ | 0.0941 | 29.0 | 522 | 0.3977 | 0.8971 |
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+ | 0.0882 | 30.0 | 540 | 0.3436 | 0.8914 |
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+ | 0.1131 | 31.0 | 558 | 0.3397 | 0.8914 |
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+ | 0.0959 | 32.0 | 576 | 0.3420 | 0.8971 |
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+ | 0.1058 | 33.0 | 594 | 0.3312 | 0.8971 |
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+ | 0.0707 | 34.0 | 612 | 0.3917 | 0.8857 |
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+ | 0.0885 | 35.0 | 630 | 0.3855 | 0.88 |
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+ | 0.0788 | 36.0 | 648 | 0.3519 | 0.8857 |
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+ | 0.112 | 37.0 | 666 | 0.3473 | 0.8914 |
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+ | 0.0588 | 38.0 | 684 | 0.3718 | 0.9029 |
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+ | 0.0963 | 39.0 | 702 | 0.4022 | 0.88 |
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+ | 0.0681 | 40.0 | 720 | 0.3574 | 0.8971 |
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+ | 0.0841 | 41.0 | 738 | 0.3621 | 0.88 |
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+ | 0.0739 | 42.0 | 756 | 0.3782 | 0.8914 |
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+ | 0.0649 | 42.5217 | 765 | 0.3766 | 0.8914 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 3.4.1
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+ - Tokenizers 0.21.1
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