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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/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-DAV24
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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-DAV24
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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: 0.8851
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+ - Accuracy: 0.7059
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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: 3e-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: 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: cosine
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+ - lr_scheduler_warmup_ratio: 0.2
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+ - num_epochs: 25
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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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+ | 6.5614 | 1.0 | 17 | 1.6096 | 0.3176 |
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+ | 6.1279 | 2.0 | 34 | 1.5651 | 0.3176 |
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+ | 5.5089 | 3.0 | 51 | 1.3188 | 0.5529 |
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+ | 4.453 | 4.0 | 68 | 1.0195 | 0.6353 |
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+ | 3.3808 | 5.0 | 85 | 0.9741 | 0.5882 |
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+ | 2.7707 | 6.0 | 102 | 0.8365 | 0.6353 |
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+ | 2.3091 | 7.0 | 119 | 0.7725 | 0.6588 |
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+ | 1.9831 | 8.0 | 136 | 0.8312 | 0.6588 |
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+ | 1.8284 | 9.0 | 153 | 0.8473 | 0.7059 |
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+ | 1.511 | 10.0 | 170 | 0.7539 | 0.7176 |
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+ | 1.2827 | 11.0 | 187 | 0.8067 | 0.7176 |
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+ | 1.2072 | 12.0 | 204 | 0.7927 | 0.7176 |
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+ | 1.2069 | 13.0 | 221 | 0.8184 | 0.6824 |
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+ | 0.9242 | 14.0 | 238 | 0.8548 | 0.7059 |
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+ | 0.9772 | 15.0 | 255 | 0.8374 | 0.7294 |
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+ | 0.8412 | 16.0 | 272 | 0.8340 | 0.7176 |
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+ | 0.8921 | 17.0 | 289 | 0.8729 | 0.6941 |
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+ | 0.7975 | 18.0 | 306 | 0.9115 | 0.7059 |
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+ | 0.8107 | 19.0 | 323 | 0.8830 | 0.6941 |
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+ | 0.7131 | 20.0 | 340 | 0.9049 | 0.6941 |
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+ | 0.6777 | 21.0 | 357 | 0.8895 | 0.7059 |
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+ | 0.6557 | 22.0 | 374 | 0.8831 | 0.7059 |
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+ | 0.6555 | 23.0 | 391 | 0.8846 | 0.7059 |
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+ | 0.7766 | 23.5455 | 400 | 0.8851 | 0.7059 |
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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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