---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: 4-classifier-finetuned-padchest
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7123519458544839
---

<!-- 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. -->

# 4-classifier-finetuned-padchest

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.
It achieves the following results on the evaluation set:
- Loss: 0.9186
- Accuracy: 0.7124

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0441        | 1.0   | 14   | 1.9084          | 0.3164   |
| 1.8716        | 2.0   | 28   | 1.6532          | 0.4484   |
| 1.4727        | 3.0   | 42   | 1.4218          | 0.5228   |
| 1.3452        | 4.0   | 56   | 1.3037          | 0.5736   |
| 1.2518        | 5.0   | 70   | 1.2799          | 0.5584   |
| 1.1646        | 6.0   | 84   | 1.1892          | 0.6244   |
| 1.1358        | 7.0   | 98   | 1.1543          | 0.6074   |
| 1.0664        | 8.0   | 112  | 1.1060          | 0.6277   |
| 1.041         | 9.0   | 126  | 1.0434          | 0.6667   |
| 1.002         | 10.0  | 140  | 1.0337          | 0.6582   |
| 0.9867        | 11.0  | 154  | 1.0373          | 0.6582   |
| 0.9485        | 12.0  | 168  | 0.9866          | 0.6887   |
| 0.9121        | 13.0  | 182  | 0.9827          | 0.6785   |
| 0.918         | 14.0  | 196  | 0.9588          | 0.7039   |
| 0.8882        | 15.0  | 210  | 0.9576          | 0.7005   |
| 0.873         | 16.0  | 224  | 0.9450          | 0.7022   |
| 0.8469        | 17.0  | 238  | 0.9266          | 0.7090   |
| 0.814         | 18.0  | 252  | 0.9463          | 0.6971   |
| 0.8206        | 19.0  | 266  | 0.9201          | 0.7090   |
| 0.8078        | 20.0  | 280  | 0.9186          | 0.7124   |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3