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# Cheese_X_ray

This model is a fine-tuned version of [barghavani/Cheese_xray](https://huggingface.co/barghavani/Cheese_xray) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1890
- Accuracy: 0.9381

## 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.5579        | 0.9882  | 63   | 0.5524          | 0.7062   |
| 0.4491        | 1.9922  | 127  | 0.4218          | 0.7062   |
| 0.3646        | 2.9961  | 191  | 0.3928          | 0.7440   |
| 0.3419        | 4.0     | 255  | 0.3827          | 0.8110   |
| 0.3546        | 4.9882  | 318  | 0.3530          | 0.8608   |
| 0.3745        | 5.9922  | 382  | 0.3298          | 0.8814   |
| 0.3323        | 6.9961  | 446  | 0.3022          | 0.8952   |
| 0.3125        | 8.0     | 510  | 0.2750          | 0.9089   |
| 0.2663        | 8.9882  | 573  | 0.2648          | 0.8883   |
| 0.2672        | 9.9922  | 637  | 0.2476          | 0.9038   |
| 0.2492        | 10.9961 | 701  | 0.2354          | 0.9278   |
| 0.2297        | 12.0    | 765  | 0.2272          | 0.9175   |
| 0.1915        | 12.9882 | 828  | 0.2126          | 0.9107   |
| 0.2071        | 13.9922 | 892  | 0.2006          | 0.9227   |
| 0.2251        | 14.9961 | 956  | 0.1806          | 0.9244   |
| 0.1979        | 16.0    | 1020 | 0.1900          | 0.9347   |
| 0.1969        | 16.9882 | 1083 | 0.2081          | 0.9192   |
| 0.2           | 17.9922 | 1147 | 0.2037          | 0.9175   |
| 0.2082        | 18.9961 | 1211 | 0.2108          | 0.9175   |
| 0.1838        | 19.7647 | 1260 | 0.1688          | 0.9330   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1

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