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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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+ datasets:
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+ - imagefolder
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: vit-base-patch16-224-in21k-finetuned-footulcer
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+ results:
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+ - task:
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+ name: Image Classification
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+ type: image-classification
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+ dataset:
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+ name: imagefolder
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+ type: imagefolder
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+ config: default
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+ split: train
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+ args: default
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+ metrics:
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+ - name: Accuracy
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+ type: accuracy
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+ value: 0.9913793103448276
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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-patch16-224-in21k-finetuned-footulcer
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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 the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0548
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+ - Accuracy: 0.9914
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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: 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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+ | No log | 0.97 | 8 | 0.6026 | 0.7069 |
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+ | 0.6438 | 1.94 | 16 | 0.5132 | 0.7328 |
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+ | 0.4569 | 2.91 | 24 | 0.4402 | 0.7586 |
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+ | 0.3098 | 4.0 | 33 | 0.2934 | 0.8448 |
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+ | 0.2204 | 4.97 | 41 | 0.2969 | 0.8879 |
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+ | 0.2204 | 5.94 | 49 | 0.1356 | 0.9655 |
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+ | 0.1668 | 6.91 | 57 | 0.0659 | 0.9914 |
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+ | 0.1531 | 8.0 | 66 | 0.0555 | 1.0 |
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+ | 0.1096 | 8.97 | 74 | 0.0913 | 0.9741 |
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+ | 0.112 | 9.94 | 82 | 0.0454 | 0.9914 |
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+ | 0.1095 | 10.91 | 90 | 0.0463 | 0.9914 |
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+ | 0.1095 | 12.0 | 99 | 0.0648 | 0.9914 |
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+ | 0.0829 | 12.97 | 107 | 0.0427 | 0.9914 |
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+ | 0.0741 | 13.94 | 115 | 0.0514 | 0.9914 |
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+ | 0.0679 | 14.55 | 120 | 0.0548 | 0.9914 |
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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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