---
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-U3-40A
  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-U3-40A

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: 0.0213
- Accuracy: 1.0

## 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        | 1.0   | 7    | 1.3292          | 0.3737   |
| 1.3407        | 2.0   | 14   | 1.1079          | 0.5152   |
| 1.3407        | 3.0   | 21   | 0.8918          | 0.6263   |
| 0.9919        | 4.0   | 28   | 0.6447          | 0.7879   |
| 0.9919        | 5.0   | 35   | 0.4502          | 0.8283   |
| 0.5761        | 6.0   | 42   | 0.2720          | 0.9192   |
| 0.3111        | 7.0   | 49   | 0.2302          | 0.9293   |
| 0.3111        | 8.0   | 56   | 0.1650          | 0.9495   |
| 0.204         | 9.0   | 63   | 0.1503          | 0.9495   |
| 0.204         | 10.0  | 70   | 0.0814          | 0.9798   |
| 0.1518        | 11.0  | 77   | 0.0604          | 0.9798   |
| 0.1272        | 12.0  | 84   | 0.1265          | 0.9495   |
| 0.1272        | 13.0  | 91   | 0.0518          | 0.9798   |
| 0.1379        | 14.0  | 98   | 0.0448          | 0.9899   |
| 0.1379        | 15.0  | 105  | 0.0361          | 0.9899   |
| 0.092         | 16.0  | 112  | 0.0322          | 0.9899   |
| 0.092         | 17.0  | 119  | 0.0213          | 1.0      |
| 0.0762        | 18.0  | 126  | 0.0469          | 0.9899   |
| 0.0954        | 19.0  | 133  | 0.0615          | 0.9899   |
| 0.0954        | 20.0  | 140  | 0.0313          | 0.9899   |
| 0.0795        | 21.0  | 147  | 0.0381          | 0.9899   |
| 0.0795        | 22.0  | 154  | 0.0138          | 1.0      |
| 0.077         | 23.0  | 161  | 0.0170          | 1.0      |
| 0.0675        | 24.0  | 168  | 0.0107          | 1.0      |
| 0.0675        | 25.0  | 175  | 0.0193          | 0.9899   |
| 0.0659        | 26.0  | 182  | 0.0255          | 0.9899   |
| 0.0659        | 27.0  | 189  | 0.0201          | 0.9899   |
| 0.0758        | 28.0  | 196  | 0.0325          | 0.9899   |
| 0.0758        | 29.0  | 203  | 0.0110          | 1.0      |
| 0.0589        | 30.0  | 210  | 0.0159          | 1.0      |
| 0.0521        | 31.0  | 217  | 0.0319          | 0.9899   |
| 0.0521        | 32.0  | 224  | 0.0294          | 0.9798   |
| 0.0618        | 33.0  | 231  | 0.0392          | 0.9798   |
| 0.0618        | 34.0  | 238  | 0.0269          | 0.9899   |
| 0.0422        | 35.0  | 245  | 0.0210          | 0.9899   |
| 0.0551        | 36.0  | 252  | 0.0178          | 0.9899   |
| 0.0551        | 37.0  | 259  | 0.0159          | 0.9899   |
| 0.0518        | 38.0  | 266  | 0.0124          | 0.9899   |
| 0.0518        | 39.0  | 273  | 0.0112          | 1.0      |
| 0.0313        | 40.0  | 280  | 0.0110          | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2