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update model card README.md

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+ ---
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+ license: apache-2.0
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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: 2-classifier-finetuned-padchest
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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: 0.6888217522658611
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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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+ # 2-classifier-finetuned-padchest
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+
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+ This model is a fine-tuned version of [nickmuchi/vit-finetuned-chest-xray-pneumonia](https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia) on the imagefolder dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0461
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+ - Accuracy: 0.6888
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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: 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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+ | 2.0026 | 1.0 | 16 | 1.7223 | 0.4320 |
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+ | 1.5584 | 2.0 | 32 | 1.4524 | 0.5619 |
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+ | 1.454 | 3.0 | 48 | 1.3117 | 0.6073 |
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+ | 1.2664 | 4.0 | 64 | 1.2396 | 0.5921 |
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+ | 1.1593 | 5.0 | 80 | 1.1685 | 0.6435 |
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+ | 1.127 | 6.0 | 96 | 1.1092 | 0.6556 |
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+ | 1.0612 | 7.0 | 112 | 1.0907 | 0.6798 |
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+ | 1.0467 | 8.0 | 128 | 1.0597 | 0.6737 |
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+ | 1.0069 | 9.0 | 144 | 1.0557 | 0.6767 |
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+ | 1.0014 | 10.0 | 160 | 1.0461 | 0.6888 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.28.0.dev0
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 2.18.0
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+ - Tokenizers 0.13.3