
<!-- 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-msn-small-lipid-invalidation-nobg

This model is a fine-tuned version of [facebook/vit-msn-small](https://huggingface.co/facebook/vit-msn-small) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1866
- Accuracy: 0.9235

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 0.5868          | 0.7059   |
| 0.583         | 2.0   | 12   | 0.2850          | 0.8706   |
| 0.583         | 3.0   | 18   | 0.3167          | 0.8647   |
| 0.4996        | 4.0   | 24   | 0.3738          | 0.8294   |
| 0.3097        | 5.0   | 30   | 0.2105          | 0.9176   |
| 0.3097        | 6.0   | 36   | 0.2695          | 0.8824   |
| 0.2893        | 7.0   | 42   | 0.2304          | 0.8941   |
| 0.2893        | 8.0   | 48   | 0.2978          | 0.8529   |
| 0.3305        | 9.0   | 54   | 0.2952          | 0.8882   |
| 0.2775        | 10.0  | 60   | 0.2661          | 0.8882   |
| 0.2775        | 11.0  | 66   | 0.2533          | 0.8824   |
| 0.223         | 12.0  | 72   | 0.2586          | 0.8882   |
| 0.223         | 13.0  | 78   | 0.2034          | 0.9176   |
| 0.216         | 14.0  | 84   | 0.1866          | 0.9235   |
| 0.1858        | 15.0  | 90   | 0.2631          | 0.8882   |
| 0.1858        | 16.0  | 96   | 0.2440          | 0.8882   |
| 0.1866        | 17.0  | 102  | 0.2480          | 0.8941   |
| 0.1866        | 18.0  | 108  | 0.3897          | 0.8647   |
| 0.1701        | 19.0  | 114  | 0.3999          | 0.8647   |
| 0.1717        | 20.0  | 120  | 0.3307          | 0.8706   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.3.2
- Tokenizers 0.19.1

invalid valid