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End of training

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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/swinv2-base-patch4-window12to16-192to256-22kto1k-ft
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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: No-Augmentation-swinv2-base
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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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+ # No-Augmentation-swinv2-base
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+
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+ This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft](https://huggingface.co/microsoft/swinv2-base-patch4-window12to16-192to256-22kto1k-ft) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9741
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+ - Accuracy: 0.7589
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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: 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: 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: 10
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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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+ | 2.3968 | 0.96 | 18 | 1.3103 | 0.5731 |
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+ | 0.8906 | 1.97 | 37 | 0.9292 | 0.6838 |
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+ | 0.4531 | 2.99 | 56 | 0.8277 | 0.7352 |
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+ | 0.2294 | 4.0 | 75 | 0.8021 | 0.7273 |
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+ | 0.1208 | 4.96 | 93 | 0.7764 | 0.7589 |
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+ | 0.0745 | 5.97 | 112 | 0.8899 | 0.7549 |
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+ | 0.0733 | 6.99 | 131 | 0.9730 | 0.7549 |
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+ | 0.0381 | 8.0 | 150 | 0.9304 | 0.7747 |
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+ | 0.0151 | 8.96 | 168 | 0.9733 | 0.7510 |
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+ | 0.0233 | 9.6 | 180 | 0.9741 | 0.7589 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.3
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+ - Pytorch 2.1.2
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+ - Datasets 2.19.1
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+ - Tokenizers 0.15.2
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