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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: google/vit-base-patch16-224-in21k
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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: vit-base-brain-dementia-detection1
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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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+ # vit-base-brain-dementia-detection1
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+
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+ This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2209
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+ - Accuracy: 0.9516
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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: 2e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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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_steps: 500
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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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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+ | 0.7193 | 1.9531 | 500 | 0.7950 | 0.6592 |
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+ | 0.249 | 3.9062 | 1000 | 0.3423 | 0.9023 |
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+ | 0.0774 | 5.8594 | 1500 | 0.1845 | 0.9492 |
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+ | 0.0306 | 7.8125 | 2000 | 0.1809 | 0.9570 |
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+ | 0.0099 | 9.7656 | 2500 | 0.1198 | 0.9717 |
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+ | 0.0065 | 11.7188 | 3000 | 0.1497 | 0.9648 |
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+ | 0.0053 | 13.6719 | 3500 | 0.1477 | 0.9668 |
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+ | 0.004 | 15.625 | 4000 | 0.1585 | 0.9629 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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+ {
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+ }
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+ {
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+ "_name_or_path": "google/vit-base-patch16-224-in21k",
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+ "ViTForImageClassification"
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+ "model_type": "vit",
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+ }
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