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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: Train-Augmentation-V2-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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+ # Train-Augmentation-V2-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: 0.9822
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+ - Accuracy: 0.8459
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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: 15
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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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+ | 0.5894 | 0.99 | 109 | 0.7123 | 0.7481 |
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+ | 0.2772 | 2.0 | 219 | 0.6394 | 0.7970 |
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+ | 0.1863 | 3.0 | 329 | 0.7819 | 0.7669 |
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+ | 0.0925 | 4.0 | 439 | 0.7062 | 0.8083 |
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+ | 0.0461 | 4.99 | 548 | 0.8637 | 0.8120 |
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+ | 0.0427 | 6.0 | 658 | 0.9080 | 0.7970 |
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+ | 0.043 | 7.0 | 768 | 1.0747 | 0.8045 |
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+ | 0.0074 | 8.0 | 878 | 0.9019 | 0.8421 |
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+ | 0.0169 | 8.99 | 987 | 0.9099 | 0.8459 |
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+ | 0.015 | 10.0 | 1097 | 0.9512 | 0.8647 |
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+ | 0.0022 | 11.0 | 1207 | 1.0051 | 0.8609 |
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+ | 0.0081 | 12.0 | 1317 | 1.0061 | 0.8308 |
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+ | 0.0013 | 12.99 | 1426 | 0.9844 | 0.8534 |
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+ | 0.0037 | 14.0 | 1536 | 0.9864 | 0.8459 |
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+ | 0.0002 | 14.9 | 1635 | 0.9822 | 0.8459 |
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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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