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# vit-base-patch16-224-ve-U11-b-80

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5456
- Accuracy: 0.8913

## 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: 5.5e-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: 0.05
- num_epochs: 80

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.3848          | 0.3696   |
| 1.3848        | 2.0   | 13   | 1.3692          | 0.5217   |
| 1.3848        | 2.92  | 19   | 1.3197          | 0.5435   |
| 1.3517        | 4.0   | 26   | 1.2264          | 0.5      |
| 1.2334        | 4.92  | 32   | 1.1280          | 0.4348   |
| 1.2334        | 6.0   | 39   | 1.0437          | 0.5435   |
| 1.073         | 6.92  | 45   | 0.9771          | 0.5870   |
| 0.9358        | 8.0   | 52   | 0.9470          | 0.6739   |
| 0.9358        | 8.92  | 58   | 0.8528          | 0.7826   |
| 0.7955        | 10.0  | 65   | 0.7839          | 0.7609   |
| 0.6429        | 10.92 | 71   | 0.7620          | 0.7391   |
| 0.6429        | 12.0  | 78   | 0.6466          | 0.8043   |
| 0.5096        | 12.92 | 84   | 0.7396          | 0.7174   |
| 0.4086        | 14.0  | 91   | 0.7335          | 0.7174   |
| 0.4086        | 14.92 | 97   | 0.6473          | 0.7391   |
| 0.3355        | 16.0  | 104  | 0.6019          | 0.7391   |
| 0.2511        | 16.92 | 110  | 0.5275          | 0.8261   |
| 0.2511        | 18.0  | 117  | 0.6069          | 0.7826   |
| 0.1925        | 18.92 | 123  | 0.6447          | 0.7826   |
| 0.2121        | 20.0  | 130  | 0.5044          | 0.8261   |
| 0.2121        | 20.92 | 136  | 0.4805          | 0.8478   |
| 0.1883        | 22.0  | 143  | 0.6723          | 0.8043   |
| 0.1883        | 22.92 | 149  | 0.7730          | 0.7391   |
| 0.1693        | 24.0  | 156  | 0.6574          | 0.7609   |
| 0.1252        | 24.92 | 162  | 0.8192          | 0.7391   |
| 0.1252        | 26.0  | 169  | 0.5984          | 0.7826   |
| 0.1439        | 26.92 | 175  | 0.7633          | 0.7826   |
| 0.137         | 28.0  | 182  | 0.6566          | 0.8478   |
| 0.137         | 28.92 | 188  | 0.6550          | 0.8261   |
| 0.1316        | 30.0  | 195  | 0.7163          | 0.7391   |
| 0.1101        | 30.92 | 201  | 0.6241          | 0.7826   |
| 0.1101        | 32.0  | 208  | 0.6360          | 0.8478   |
| 0.0947        | 32.92 | 214  | 0.5273          | 0.8696   |
| 0.0885        | 34.0  | 221  | 0.6579          | 0.8261   |
| 0.0885        | 34.92 | 227  | 0.5920          | 0.8696   |
| 0.0967        | 36.0  | 234  | 0.6779          | 0.8261   |
| 0.0812        | 36.92 | 240  | 0.7354          | 0.8043   |
| 0.0812        | 38.0  | 247  | 0.6825          | 0.8261   |
| 0.0752        | 38.92 | 253  | 0.6348          | 0.8478   |
| 0.0757        | 40.0  | 260  | 0.7726          | 0.8043   |
| 0.0757        | 40.92 | 266  | 0.6737          | 0.8261   |
| 0.086         | 42.0  | 273  | 0.6738          | 0.7826   |
| 0.086         | 42.92 | 279  | 0.7295          | 0.7609   |
| 0.0533        | 44.0  | 286  | 0.6897          | 0.8261   |
| 0.0574        | 44.92 | 292  | 0.6427          | 0.8261   |
| 0.0574        | 46.0  | 299  | 0.6471          | 0.8261   |
| 0.0739        | 46.92 | 305  | 0.6645          | 0.8261   |
| 0.0849        | 48.0  | 312  | 0.6858          | 0.8043   |
| 0.0849        | 48.92 | 318  | 0.7475          | 0.8043   |
| 0.0719        | 50.0  | 325  | 0.6735          | 0.8261   |
| 0.0434        | 50.92 | 331  | 0.6892          | 0.8478   |
| 0.0434        | 52.0  | 338  | 0.6820          | 0.8478   |
| 0.0564        | 52.92 | 344  | 0.6677          | 0.8478   |
| 0.0408        | 54.0  | 351  | 0.7379          | 0.8043   |
| 0.0408        | 54.92 | 357  | 0.5456          | 0.8913   |
| 0.0464        | 56.0  | 364  | 0.7951          | 0.7826   |
| 0.0463        | 56.92 | 370  | 0.6356          | 0.8478   |
| 0.0463        | 58.0  | 377  | 0.7529          | 0.8261   |
| 0.0361        | 58.92 | 383  | 0.8017          | 0.8261   |
| 0.0457        | 60.0  | 390  | 0.7877          | 0.8478   |
| 0.0457        | 60.92 | 396  | 0.8019          | 0.7826   |
| 0.0371        | 62.0  | 403  | 0.8015          | 0.8043   |
| 0.0371        | 62.92 | 409  | 0.8487          | 0.8043   |
| 0.0452        | 64.0  | 416  | 0.9401          | 0.7609   |
| 0.0455        | 64.92 | 422  | 0.9647          | 0.7609   |
| 0.0455        | 66.0  | 429  | 0.8958          | 0.7609   |
| 0.0408        | 66.92 | 435  | 0.8531          | 0.7826   |
| 0.0418        | 68.0  | 442  | 0.8206          | 0.8043   |
| 0.0418        | 68.92 | 448  | 0.8045          | 0.8043   |
| 0.0424        | 70.0  | 455  | 0.8090          | 0.8043   |
| 0.038         | 70.92 | 461  | 0.7902          | 0.8043   |
| 0.038         | 72.0  | 468  | 0.8008          | 0.8261   |
| 0.0401        | 72.92 | 474  | 0.8122          | 0.8043   |
| 0.0347        | 73.85 | 480  | 0.8161          | 0.8043   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0

avanzada leve moderada no dmae