---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: vit-pneumonia
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: chest-xray-classification
      type: chest-xray-classification
      config: full
      split: validation
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.976824034334764
---

<!-- 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-pneumonia

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 chest-xray-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1086
- Accuracy: 0.9768

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0357        | 1.0   | 192  | 0.0955          | 0.9691   |
| 0.0404        | 2.0   | 384  | 0.0720          | 0.9751   |
| 0.0546        | 3.0   | 576  | 0.2275          | 0.9468   |
| 0.0113        | 4.0   | 768  | 0.1386          | 0.9648   |
| 0.0101        | 5.0   | 960  | 0.1212          | 0.9708   |
| 0.0003        | 6.0   | 1152 | 0.0929          | 0.9777   |
| 0.0002        | 7.0   | 1344 | 0.1051          | 0.9777   |
| 0.0002        | 8.0   | 1536 | 0.1075          | 0.9777   |
| 0.0002        | 9.0   | 1728 | 0.1084          | 0.9768   |
| 0.0002        | 10.0  | 1920 | 0.1086          | 0.9768   |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2