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# vit-base-patch16-224-in21k-finetuned-lf-invalidation

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1798
- Accuracy: 0.9511

## 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: 50

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6773        | 0.9796  | 12   | 0.6550          | 0.5681   |
| 0.5982        | 1.9592  | 24   | 0.5839          | 0.6362   |
| 0.479         | 2.9388  | 36   | 0.4356          | 0.8894   |
| 0.3862        | 4.0     | 49   | 0.2807          | 0.9362   |
| 0.2498        | 4.9796  | 61   | 0.2599          | 0.9128   |
| 0.2836        | 5.9592  | 73   | 0.5015          | 0.7745   |
| 0.2641        | 6.9388  | 85   | 0.5500          | 0.7340   |
| 0.2716        | 8.0     | 98   | 0.3083          | 0.8787   |
| 0.2382        | 8.9796  | 110  | 0.2885          | 0.8936   |
| 0.1985        | 9.9592  | 122  | 0.1798          | 0.9511   |
| 0.2174        | 10.9388 | 134  | 0.3060          | 0.8766   |
| 0.2372        | 12.0    | 147  | 0.3084          | 0.8702   |
| 0.2164        | 12.9796 | 159  | 0.2667          | 0.9021   |
| 0.2106        | 13.9592 | 171  | 0.3747          | 0.8447   |
| 0.1956        | 14.9388 | 183  | 0.5105          | 0.7851   |
| 0.2154        | 16.0    | 196  | 0.5683          | 0.7787   |
| 0.179         | 16.9796 | 208  | 0.4279          | 0.8340   |
| 0.2548        | 17.9592 | 220  | 0.6493          | 0.7404   |
| 0.236         | 18.9388 | 232  | 0.3860          | 0.8340   |
| 0.2121        | 20.0    | 245  | 0.5826          | 0.7766   |
| 0.1691        | 20.9796 | 257  | 0.3195          | 0.8638   |
| 0.1824        | 21.9592 | 269  | 0.3772          | 0.8404   |
| 0.1733        | 22.9388 | 281  | 0.5182          | 0.7936   |
| 0.1837        | 24.0    | 294  | 0.4924          | 0.8149   |
| 0.1274        | 24.9796 | 306  | 0.3895          | 0.8447   |
| 0.1415        | 25.9592 | 318  | 0.3662          | 0.8532   |
| 0.186         | 26.9388 | 330  | 0.4347          | 0.8447   |
| 0.1403        | 28.0    | 343  | 0.4490          | 0.8383   |
| 0.1635        | 28.9796 | 355  | 0.7771          | 0.7085   |
| 0.2135        | 29.9592 | 367  | 0.3503          | 0.8702   |
| 0.1456        | 30.9388 | 379  | 0.3815          | 0.8617   |
| 0.1634        | 32.0    | 392  | 0.2810          | 0.9      |
| 0.1308        | 32.9796 | 404  | 0.4643          | 0.8383   |
| 0.163         | 33.9592 | 416  | 0.3337          | 0.8787   |
| 0.1736        | 34.9388 | 428  | 0.4070          | 0.8553   |
| 0.1638        | 36.0    | 441  | 0.4142          | 0.8574   |
| 0.1488        | 36.9796 | 453  | 0.5039          | 0.8170   |
| 0.148         | 37.9592 | 465  | 0.5767          | 0.7745   |
| 0.1741        | 38.9388 | 477  | 0.4842          | 0.8255   |
| 0.1338        | 40.0    | 490  | 0.7236          | 0.7234   |
| 0.1302        | 40.9796 | 502  | 0.5295          | 0.8043   |
| 0.141         | 41.9592 | 514  | 0.5294          | 0.8085   |
| 0.1461        | 42.9388 | 526  | 0.5485          | 0.7979   |
| 0.1006        | 44.0    | 539  | 0.5453          | 0.7915   |
| 0.1317        | 44.9796 | 551  | 0.5930          | 0.7681   |
| 0.1069        | 45.9592 | 563  | 0.4976          | 0.8170   |
| 0.1531        | 46.9388 | 575  | 0.5105          | 0.8064   |
| 0.155         | 48.0    | 588  | 0.6128          | 0.7638   |
| 0.1237        | 48.9796 | 600  | 0.6180          | 0.7617   |


### Framework versions

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

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