---
license: apache-2.0
base_model: barghavani/Cheese_xray
tags:
- generated_from_trainer
datasets:
- chest-xray-classification
metrics:
- accuracy
model-index:
- name: Cheese_xray
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: chest-xray-classification
      type: chest-xray-classification
      config: full
      split: test
      args: full
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8883161512027491
---

<!-- 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. -->

# Cheese_xray

This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on the chest-xray-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2827
- Accuracy: 0.8883

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3993        | 0.99  | 63   | 0.4364          | 0.7165   |
| 0.3454        | 1.99  | 127  | 0.3947          | 0.7680   |
| 0.3327        | 3.0   | 191  | 0.3582          | 0.8591   |
| 0.3329        | 4.0   | 255  | 0.3371          | 0.8746   |
| 0.2992        | 4.99  | 318  | 0.3449          | 0.8643   |
| 0.3289        | 5.99  | 382  | 0.3172          | 0.8832   |
| 0.3309        | 7.0   | 446  | 0.2956          | 0.8935   |
| 0.2875        | 8.0   | 510  | 0.2911          | 0.8883   |
| 0.2764        | 8.99  | 573  | 0.2884          | 0.9124   |
| 0.265         | 9.88  | 630  | 0.2827          | 0.8883   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0