---
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-U5-42
  results: []
---

<!-- 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-U5-42

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7345
- Accuracy: 0.8333

## 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: 42

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.9   | 7    | 1.2858          | 0.5      |
| 1.3455        | 1.94  | 15   | 1.1091          | 0.4833   |
| 1.3455        | 2.97  | 23   | 0.8518          | 0.5833   |
| 1.0067        | 4.0   | 31   | 0.7317          | 0.7167   |
| 0.6085        | 4.9   | 38   | 0.6949          | 0.75     |
| 0.6085        | 5.94  | 46   | 0.6633          | 0.75     |
| 0.3389        | 6.97  | 54   | 0.6791          | 0.7667   |
| 0.1977        | 8.0   | 62   | 0.7010          | 0.7333   |
| 0.1977        | 8.9   | 69   | 0.6970          | 0.75     |
| 0.1496        | 9.94  | 77   | 0.6984          | 0.8      |
| 0.1194        | 10.97 | 85   | 0.9061          | 0.7333   |
| 0.1194        | 12.0  | 93   | 0.8720          | 0.75     |
| 0.109         | 12.9  | 100  | 0.8439          | 0.7833   |
| 0.0902        | 13.94 | 108  | 0.7345          | 0.8333   |
| 0.0902        | 14.97 | 116  | 0.8420          | 0.7833   |
| 0.0938        | 16.0  | 124  | 0.7994          | 0.75     |
| 0.0938        | 16.9  | 131  | 0.8341          | 0.8      |
| 0.0862        | 17.94 | 139  | 0.7239          | 0.8      |
| 0.0864        | 18.97 | 147  | 0.8485          | 0.7833   |
| 0.0864        | 20.0  | 155  | 0.8948          | 0.8      |
| 0.065         | 20.9  | 162  | 0.8681          | 0.8167   |
| 0.0793        | 21.94 | 170  | 0.8226          | 0.8167   |
| 0.0793        | 22.97 | 178  | 0.7495          | 0.8333   |
| 0.0629        | 24.0  | 186  | 0.8814          | 0.7667   |
| 0.0666        | 24.9  | 193  | 0.7739          | 0.8167   |
| 0.0666        | 25.94 | 201  | 0.9246          | 0.7833   |
| 0.0571        | 26.97 | 209  | 0.8077          | 0.8333   |
| 0.0519        | 28.0  | 217  | 0.8975          | 0.7833   |
| 0.0519        | 28.9  | 224  | 0.9199          | 0.7833   |
| 0.0523        | 29.94 | 232  | 0.8512          | 0.8      |
| 0.0548        | 30.97 | 240  | 0.9377          | 0.8167   |
| 0.0548        | 32.0  | 248  | 0.8213          | 0.8167   |
| 0.0576        | 32.9  | 255  | 0.8384          | 0.8167   |
| 0.0576        | 33.94 | 263  | 0.8664          | 0.8      |
| 0.0381        | 34.97 | 271  | 0.8818          | 0.8      |
| 0.0338        | 36.0  | 279  | 0.9106          | 0.7833   |
| 0.0338        | 36.9  | 286  | 0.9057          | 0.7833   |
| 0.0443        | 37.94 | 294  | 0.9012          | 0.7833   |


### Framework versions

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