
<!-- 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-finetuned-lf-invalidation

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: 0.2442
- Accuracy: 0.9234

## 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 6    | 0.7163          | 0.4      |
| 0.7           | 1.92  | 12   | 0.4886          | 0.8234   |
| 0.7           | 2.88  | 18   | 0.4683          | 0.7596   |
| 0.3793        | 4.0   | 25   | 0.3421          | 0.8447   |
| 0.383         | 4.96  | 31   | 0.2535          | 0.9191   |
| 0.383         | 5.92  | 37   | 0.2442          | 0.9234   |
| 0.3658        | 6.88  | 43   | 0.3795          | 0.8404   |
| 0.2601        | 8.0   | 50   | 0.3831          | 0.8383   |
| 0.2601        | 8.96  | 56   | 0.3993          | 0.8191   |
| 0.26          | 9.92  | 62   | 0.2265          | 0.8979   |
| 0.26          | 10.88 | 68   | 0.5355          | 0.7319   |
| 0.3376        | 12.0  | 75   | 0.3881          | 0.8043   |
| 0.248         | 12.96 | 81   | 0.2618          | 0.8979   |
| 0.248         | 13.92 | 87   | 0.5545          | 0.7362   |
| 0.2133        | 14.88 | 93   | 0.9307          | 0.5489   |
| 0.2576        | 16.0  | 100  | 0.4236          | 0.8149   |
| 0.2576        | 16.96 | 106  | 0.4333          | 0.8106   |
| 0.2466        | 17.92 | 112  | 0.8464          | 0.6128   |
| 0.2466        | 18.88 | 118  | 0.7970          | 0.6489   |
| 0.228         | 20.0  | 125  | 0.3522          | 0.8660   |
| 0.2542        | 20.96 | 131  | 0.5095          | 0.7872   |
| 0.2542        | 21.92 | 137  | 0.4808          | 0.8021   |
| 0.2032        | 22.88 | 143  | 0.5805          | 0.7340   |
| 0.1998        | 24.0  | 150  | 0.3987          | 0.8319   |
| 0.1998        | 24.96 | 156  | 0.4889          | 0.7894   |
| 0.1565        | 25.92 | 162  | 0.8003          | 0.6468   |
| 0.1565        | 26.88 | 168  | 0.4740          | 0.7936   |
| 0.1934        | 28.0  | 175  | 0.4442          | 0.8319   |
| 0.1878        | 28.96 | 181  | 0.7115          | 0.7021   |
| 0.1878        | 29.92 | 187  | 0.4234          | 0.8277   |
| 0.1848        | 30.88 | 193  | 0.6975          | 0.6957   |
| 0.1705        | 32.0  | 200  | 0.2965          | 0.8894   |
| 0.1705        | 32.96 | 206  | 0.8020          | 0.6766   |
| 0.1744        | 33.92 | 212  | 0.7330          | 0.6979   |
| 0.1744        | 34.88 | 218  | 1.0977          | 0.5723   |
| 0.1707        | 36.0  | 225  | 1.0648          | 0.5894   |
| 0.1719        | 36.96 | 231  | 0.8495          | 0.6404   |
| 0.1719        | 37.92 | 237  | 0.3177          | 0.8787   |
| 0.1839        | 38.88 | 243  | 0.4839          | 0.7894   |
| 0.1544        | 40.0  | 250  | 0.4100          | 0.8362   |
| 0.1544        | 40.96 | 256  | 0.6012          | 0.7553   |
| 0.135         | 41.92 | 262  | 0.6832          | 0.7213   |
| 0.135         | 42.88 | 268  | 0.6663          | 0.7170   |
| 0.14          | 44.0  | 275  | 0.6219          | 0.7383   |
| 0.151         | 44.96 | 281  | 0.9176          | 0.6149   |
| 0.151         | 45.92 | 287  | 0.8830          | 0.6404   |
| 0.1284        | 46.88 | 293  | 0.7249          | 0.7043   |
| 0.1586        | 48.0  | 300  | 0.7146          | 0.7043   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1

invalid valid