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# vit-base-patch16-224-in21k-finetuned-papsmear

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: 0.2825
- Accuracy: 0.9338

## 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        | 0.9231  | 9    | 1.7346          | 0.2647   |
| 1.7645        | 1.9487  | 19   | 1.6152          | 0.3088   |
| 1.661         | 2.9744  | 29   | 1.4663          | 0.4118   |
| 1.496         | 4.0     | 39   | 1.2989          | 0.4853   |
| 1.3097        | 4.9231  | 48   | 1.1491          | 0.5588   |
| 1.091         | 5.9487  | 58   | 0.9933          | 0.7206   |
| 0.9088        | 6.9744  | 68   | 0.9171          | 0.6985   |
| 0.7858        | 8.0     | 78   | 0.8301          | 0.7721   |
| 0.7016        | 8.9231  | 87   | 0.7925          | 0.7353   |
| 0.6136        | 9.9487  | 97   | 0.6992          | 0.7647   |
| 0.532         | 10.9744 | 107  | 0.6401          | 0.8309   |
| 0.5018        | 12.0    | 117  | 0.5787          | 0.8382   |
| 0.4279        | 12.9231 | 126  | 0.6130          | 0.8088   |
| 0.4116        | 13.9487 | 136  | 0.5090          | 0.8382   |
| 0.3848        | 14.9744 | 146  | 0.5165          | 0.8676   |
| 0.3449        | 16.0    | 156  | 0.4843          | 0.8382   |
| 0.3008        | 16.9231 | 165  | 0.5460          | 0.8456   |
| 0.2797        | 17.9487 | 175  | 0.4985          | 0.8309   |
| 0.2696        | 18.9744 | 185  | 0.5586          | 0.8456   |
| 0.2633        | 20.0    | 195  | 0.4349          | 0.9044   |
| 0.2569        | 20.9231 | 204  | 0.4017          | 0.8897   |
| 0.27          | 21.9487 | 214  | 0.4758          | 0.8603   |
| 0.2706        | 22.9744 | 224  | 0.4133          | 0.8897   |
| 0.2211        | 24.0    | 234  | 0.3844          | 0.9118   |
| 0.1977        | 24.9231 | 243  | 0.3497          | 0.9265   |
| 0.1969        | 25.9487 | 253  | 0.3736          | 0.9044   |
| 0.1776        | 26.9744 | 263  | 0.3797          | 0.9044   |
| 0.1787        | 28.0    | 273  | 0.3949          | 0.8897   |
| 0.18          | 28.9231 | 282  | 0.3278          | 0.9265   |
| 0.1797        | 29.9487 | 292  | 0.3615          | 0.9044   |
| 0.1665        | 30.9744 | 302  | 0.4174          | 0.8603   |
| 0.163         | 32.0    | 312  | 0.3574          | 0.8971   |
| 0.1498        | 32.9231 | 321  | 0.3591          | 0.9044   |
| 0.1405        | 33.9487 | 331  | 0.3017          | 0.9191   |
| 0.155         | 34.9744 | 341  | 0.3303          | 0.9265   |
| 0.1519        | 36.0    | 351  | 0.3559          | 0.8971   |
| 0.1415        | 36.9231 | 360  | 0.2890          | 0.9191   |
| 0.1256        | 37.9487 | 370  | 0.3445          | 0.8897   |
| 0.1217        | 38.9744 | 380  | 0.3435          | 0.9118   |
| 0.1285        | 40.0    | 390  | 0.3025          | 0.9191   |
| 0.1285        | 40.9231 | 399  | 0.3602          | 0.8824   |
| 0.1301        | 41.9487 | 409  | 0.3336          | 0.8897   |
| 0.1243        | 42.9744 | 419  | 0.2825          | 0.9338   |
| 0.1191        | 44.0    | 429  | 0.2835          | 0.9265   |
| 0.1221        | 44.9231 | 438  | 0.2724          | 0.9191   |
| 0.1151        | 45.9487 | 448  | 0.2708          | 0.9191   |
| 0.1195        | 46.1538 | 450  | 0.2707          | 0.9191   |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1

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