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swinv2-tiny-patch4-window8-256-dmae-humeda-DAV19

Image Classification
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swinv2
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  2. model.safetensors +1 -1
  3. runs/Jan21_06-34-31_777c566d7676/events.out.tfevents.1737441299.777c566d7676.18204.0 +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-DAV19
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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-DAV19
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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: 1.4438
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+ - Accuracy: 0.7308
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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: 7e-05
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+ - train_batch_size: 64
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+ - eval_batch_size: 64
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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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+ - lr_scheduler_warmup_ratio: 0.3
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+ - num_epochs: 42
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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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+ | 1.6103 | 1.0 | 22 | 1.6051 | 0.2885 |
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+ | 1.4727 | 2.0 | 44 | 1.4581 | 0.4808 |
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+ | 1.0885 | 3.0 | 66 | 1.1148 | 0.5385 |
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+ | 0.8317 | 4.0 | 88 | 1.1753 | 0.4808 |
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+ | 0.5767 | 5.0 | 110 | 1.0842 | 0.5192 |
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+ | 0.4983 | 6.0 | 132 | 0.9595 | 0.5769 |
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+ | 0.4392 | 7.0 | 154 | 0.9108 | 0.6538 |
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+ | 0.38 | 8.0 | 176 | 0.7973 | 0.6923 |
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+ | 0.367 | 9.0 | 198 | 0.8772 | 0.6346 |
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+ | 0.2892 | 10.0 | 220 | 0.9240 | 0.6346 |
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+ | 0.2627 | 11.0 | 242 | 1.1102 | 0.6154 |
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+ | 0.1956 | 12.0 | 264 | 0.8497 | 0.7115 |
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+ | 0.2529 | 13.0 | 286 | 0.9588 | 0.6923 |
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+ | 0.1933 | 14.0 | 308 | 1.4496 | 0.5962 |
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+ | 0.2023 | 15.0 | 330 | 1.2467 | 0.6346 |
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+ | 0.1725 | 16.0 | 352 | 1.1693 | 0.6731 |
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+ | 0.1604 | 17.0 | 374 | 1.1374 | 0.6346 |
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+ | 0.1909 | 18.0 | 396 | 0.9065 | 0.7115 |
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+ | 0.1577 | 19.0 | 418 | 1.1488 | 0.6538 |
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+ | 0.1323 | 20.0 | 440 | 1.3994 | 0.6923 |
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+ | 0.1342 | 21.0 | 462 | 1.1350 | 0.6731 |
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+ | 0.1024 | 22.0 | 484 | 1.2422 | 0.6538 |
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+ | 0.1054 | 23.0 | 506 | 1.0670 | 0.75 |
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+ | 0.0809 | 24.0 | 528 | 1.2367 | 0.6731 |
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+ | 0.0856 | 25.0 | 550 | 1.1758 | 0.7308 |
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+ | 0.0781 | 26.0 | 572 | 1.1735 | 0.6731 |
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+ | 0.1136 | 27.0 | 594 | 1.5008 | 0.6923 |
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+ | 0.0784 | 28.0 | 616 | 1.2966 | 0.7308 |
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+ | 0.0648 | 29.0 | 638 | 1.2018 | 0.7115 |
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+ | 0.0941 | 30.0 | 660 | 1.0879 | 0.6731 |
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+ | 0.0654 | 31.0 | 682 | 1.2646 | 0.7115 |
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+ | 0.0967 | 32.0 | 704 | 1.0537 | 0.75 |
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+ | 0.0717 | 33.0 | 726 | 1.4332 | 0.7115 |
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+ | 0.0715 | 34.0 | 748 | 1.2683 | 0.7308 |
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+ | 0.0773 | 35.0 | 770 | 1.3363 | 0.6731 |
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+ | 0.0767 | 36.0 | 792 | 1.3192 | 0.6731 |
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+ | 0.0343 | 37.0 | 814 | 1.2926 | 0.7115 |
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+ | 0.0524 | 38.0 | 836 | 1.4072 | 0.7115 |
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+ | 0.052 | 39.0 | 858 | 1.4377 | 0.6923 |
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+ | 0.0247 | 40.0 | 880 | 1.4420 | 0.6923 |
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+ | 0.0256 | 41.0 | 902 | 1.4403 | 0.7115 |
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+ | 0.0384 | 42.0 | 924 | 1.4438 | 0.7308 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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