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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-DAV10
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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-DAV10
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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: 1.0099
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+ - Accuracy: 0.6731
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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: 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: 0.1
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+ - num_epochs: 30
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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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+ | No log | 0.8421 | 4 | 1.5825 | 0.2885 |
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+ | No log | 1.8421 | 8 | 1.4864 | 0.5385 |
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+ | No log | 2.8421 | 12 | 1.3187 | 0.5577 |
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+ | No log | 3.8421 | 16 | 1.0843 | 0.6731 |
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+ | No log | 4.8421 | 20 | 1.0044 | 0.5962 |
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+ | No log | 5.8421 | 24 | 0.8914 | 0.6346 |
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+ | No log | 6.8421 | 28 | 0.9119 | 0.5769 |
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+ | No log | 7.8421 | 32 | 0.9379 | 0.6538 |
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+ | No log | 8.8421 | 36 | 0.9471 | 0.6154 |
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+ | No log | 9.8421 | 40 | 0.9565 | 0.6538 |
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+ | No log | 10.8421 | 44 | 0.9581 | 0.6923 |
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+ | No log | 11.8421 | 48 | 0.9655 | 0.6923 |
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+ | 4.2193 | 12.8421 | 52 | 0.9880 | 0.7115 |
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+ | 4.2193 | 13.8421 | 56 | 0.9557 | 0.6923 |
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+ | 4.2193 | 14.8421 | 60 | 0.9275 | 0.6538 |
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+ | 4.2193 | 15.8421 | 64 | 1.0216 | 0.5769 |
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+ | 4.2193 | 16.8421 | 68 | 0.9646 | 0.6346 |
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+ | 4.2193 | 17.8421 | 72 | 0.9957 | 0.6731 |
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+ | 4.2193 | 18.8421 | 76 | 1.0366 | 0.6346 |
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+ | 4.2193 | 19.8421 | 80 | 0.9978 | 0.6538 |
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+ | 4.2193 | 20.8421 | 84 | 0.9941 | 0.6731 |
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+ | 4.2193 | 21.8421 | 88 | 1.0063 | 0.6923 |
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+ | 4.2193 | 22.8421 | 92 | 1.0114 | 0.6731 |
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+ | 4.2193 | 23.8421 | 96 | 1.0134 | 0.6731 |
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+ | 1.6367 | 24.8421 | 100 | 1.0097 | 0.6731 |
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+ | 1.6367 | 25.8421 | 104 | 1.0084 | 0.6731 |
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+ | 1.6367 | 26.8421 | 108 | 1.0097 | 0.6731 |
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+ | 1.6367 | 27.8421 | 112 | 1.0102 | 0.6731 |
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+ | 1.6367 | 28.8421 | 116 | 1.0100 | 0.6731 |
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+ | 1.6367 | 29.8421 | 120 | 1.0099 | 0.6731 |
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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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