---
license: apache-2.0
tags:
- generated_from_trainer
base_model: google/vit-base-patch16-224-in21k
metrics:
- accuracy
model-index:
- name: vit-xray-pneumonia-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-xray-pneumonia-classification

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.
It achieves the following results on the evaluation set:
- Loss: 0.0740
- Accuracy: 0.9734

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.4843        | 0.9882  | 63   | 0.1954          | 0.9408   |
| 0.1986        | 1.9922  | 127  | 0.1483          | 0.9494   |
| 0.1694        | 2.9961  | 191  | 0.1316          | 0.9459   |
| 0.1368        | 4.0     | 255  | 0.1207          | 0.9554   |
| 0.1399        | 4.9882  | 318  | 0.1738          | 0.9296   |
| 0.1203        | 5.9922  | 382  | 0.0966          | 0.9631   |
| 0.1085        | 6.9961  | 446  | 0.0956          | 0.9631   |
| 0.1046        | 8.0     | 510  | 0.0952          | 0.9665   |
| 0.0883        | 8.9882  | 573  | 0.0990          | 0.9665   |
| 0.0773        | 9.9922  | 637  | 0.0896          | 0.9717   |
| 0.0815        | 10.9961 | 701  | 0.1084          | 0.9605   |
| 0.0793        | 12.0    | 765  | 0.0767          | 0.9742   |
| 0.0778        | 12.9882 | 828  | 0.0885          | 0.9691   |
| 0.0609        | 13.9922 | 892  | 0.0778          | 0.9708   |
| 0.0685        | 14.8235 | 945  | 0.0740          | 0.9734   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1