---
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
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# 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: 0.1602
- Accuracy: 0.9313

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4638        | 0.9882 | 63   | 0.2024          | 0.9236   |
| 0.1987        | 1.9922 | 127  | 0.1342          | 0.9588   |
| 0.1637        | 2.9961 | 191  | 0.1534          | 0.9442   |
| 0.16          | 4.0    | 255  | 0.1365          | 0.9485   |
| 0.1344        | 4.9882 | 318  | 0.1602          | 0.9313   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1