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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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base_model: google/vit-base-patch16-224-in21k
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metrics:
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- accuracy
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model-index:
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- name: vit-xray-pneumonia-classification
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results: []
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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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# vit-xray-pneumonia-classification
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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: 0.0740
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- Accuracy: 0.9734
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|
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| 0.4843 | 0.9882 | 63 | 0.1954 | 0.9408 |
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| 0.1986 | 1.9922 | 127 | 0.1483 | 0.9494 |
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| 0.1694 | 2.9961 | 191 | 0.1316 | 0.9459 |
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| 0.1368 | 4.0 | 255 | 0.1207 | 0.9554 |
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| 0.1399 | 4.9882 | 318 | 0.1738 | 0.9296 |
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| 0.1203 | 5.9922 | 382 | 0.0966 | 0.9631 |
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| 0.1085 | 6.9961 | 446 | 0.0956 | 0.9631 |
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| 0.1046 | 8.0 | 510 | 0.0952 | 0.9665 |
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| 0.0883 | 8.9882 | 573 | 0.0990 | 0.9665 |
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| 0.0773 | 9.9922 | 637 | 0.0896 | 0.9717 |
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| 0.0815 | 10.9961 | 701 | 0.1084 | 0.9605 |
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| 0.0793 | 12.0 | 765 | 0.0767 | 0.9742 |
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| 0.0778 | 12.9882 | 828 | 0.0885 | 0.9691 |
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| 0.0609 | 13.9922 | 892 | 0.0778 | 0.9708 |
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| 0.0685 | 14.8235 | 945 | 0.0740 | 0.9734 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.3.0
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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