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End of training

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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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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: Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k
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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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+ # Psoriasis-Project-Aug-M2-beit-base-patch16-224-pt22k-ft22k
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+
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0042
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+ - Accuracy: 1.0
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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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+ | 1.1065 | 0.99 | 36 | 0.3867 | 0.9167 |
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+ | 0.2495 | 1.99 | 72 | 0.1087 | 0.9583 |
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+ | 0.1026 | 2.98 | 108 | 0.0239 | 1.0 |
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+ | 0.039 | 4.0 | 145 | 0.0605 | 0.9583 |
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+ | 0.0188 | 4.99 | 181 | 0.1663 | 0.9375 |
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+ | 0.0165 | 5.99 | 217 | 0.0047 | 1.0 |
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+ | 0.0047 | 6.98 | 253 | 0.0028 | 1.0 |
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+ | 0.005 | 8.0 | 290 | 0.0043 | 1.0 |
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+ | 0.0022 | 8.99 | 326 | 0.0061 | 1.0 |
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+ | 0.0015 | 9.93 | 360 | 0.0042 | 1.0 |
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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 2.18.0
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+ - Tokenizers 0.15.2
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