---
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-dmae-va-U5-40
  results: []
datasets:
- Augusto777/dmae-ve-U5
---

<!-- 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-base-patch16-224-dmae-va-U5-40

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on Augusto777/dmae-ve-U5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0367
- Accuracy: 0.8166

## 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: 40

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.92  | 6    | 1.4236          | 0.3605   |
| 1.3165        | 2.0   | 13   | 1.1072          | 0.5306   |
| 1.3165        | 2.92  | 19   | 0.9370          | 0.6463   |
| 0.93          | 4.0   | 26   | 0.6870          | 0.7687   |
| 0.93          | 4.92  | 32   | 0.4743          | 0.8163   |
| 0.5368        | 6.0   | 39   | 0.2825          | 0.9184   |
| 0.5368        | 6.92  | 45   | 0.2066          | 0.9524   |
| 0.2989        | 8.0   | 52   | 0.1224          | 0.9728   |
| 0.2989        | 8.92  | 58   | 0.1453          | 0.9592   |
| 0.1746        | 10.0  | 65   | 0.0367          | 1.0      |
| 0.1746        | 10.92 | 71   | 0.0616          | 0.9864   |
| 0.1596        | 12.0  | 78   | 0.0234          | 1.0      |
| 0.1094        | 12.92 | 84   | 0.0298          | 1.0      |
| 0.1094        | 14.0  | 91   | 0.0444          | 0.9932   |
| 0.1123        | 14.92 | 97   | 0.0251          | 1.0      |
| 0.1123        | 16.0  | 104  | 0.0185          | 1.0      |
| 0.0761        | 16.92 | 110  | 0.0159          | 1.0      |
| 0.0761        | 18.0  | 117  | 0.0180          | 1.0      |
| 0.0743        | 18.92 | 123  | 0.0111          | 1.0      |
| 0.0743        | 20.0  | 130  | 0.0134          | 1.0      |
| 0.072         | 20.92 | 136  | 0.0123          | 1.0      |
| 0.072         | 22.0  | 143  | 0.0100          | 1.0      |
| 0.0744        | 22.92 | 149  | 0.0074          | 1.0      |
| 0.0688        | 24.0  | 156  | 0.0064          | 1.0      |
| 0.0688        | 24.92 | 162  | 0.0070          | 1.0      |
| 0.0737        | 26.0  | 169  | 0.0064          | 1.0      |
| 0.0737        | 26.92 | 175  | 0.0055          | 1.0      |
| 0.053         | 28.0  | 182  | 0.0075          | 1.0      |
| 0.053         | 28.92 | 188  | 0.0046          | 1.0      |
| 0.0677        | 30.0  | 195  | 0.0046          | 1.0      |
| 0.0677        | 30.92 | 201  | 0.0098          | 1.0      |
| 0.055         | 32.0  | 208  | 0.0085          | 1.0      |
| 0.055         | 32.92 | 214  | 0.0056          | 1.0      |
| 0.0576        | 34.0  | 221  | 0.0059          | 1.0      |
| 0.0576        | 34.92 | 227  | 0.0054          | 1.0      |
| 0.0697        | 36.0  | 234  | 0.0055          | 1.0      |
| 0.0415        | 36.92 | 240  | 0.0056          | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2