---
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-da-40B
  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-da-40B

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: 0.2421
- Accuracy: 0.9302

## 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  | 3    | 1.4669          | 0.3256   |
| No log        | 1.85  | 6    | 1.2689          | 0.4419   |
| No log        | 2.77  | 9    | 1.1591          | 0.4651   |
| 1.3901        | 4.0   | 13   | 0.9778          | 0.5814   |
| 1.3901        | 4.92  | 16   | 0.8885          | 0.6512   |
| 1.3901        | 5.85  | 19   | 0.7885          | 0.6512   |
| 0.9794        | 6.77  | 22   | 0.6854          | 0.7442   |
| 0.9794        | 8.0   | 26   | 0.5822          | 0.7674   |
| 0.9794        | 8.92  | 29   | 0.4929          | 0.8605   |
| 0.6573        | 9.85  | 32   | 0.4822          | 0.8605   |
| 0.6573        | 10.77 | 35   | 0.4529          | 0.8372   |
| 0.6573        | 12.0  | 39   | 0.4203          | 0.7907   |
| 0.4166        | 12.92 | 42   | 0.3889          | 0.8605   |
| 0.4166        | 13.85 | 45   | 0.3697          | 0.8605   |
| 0.4166        | 14.77 | 48   | 0.3991          | 0.8140   |
| 0.3376        | 16.0  | 52   | 0.3038          | 0.9070   |
| 0.3376        | 16.92 | 55   | 0.3139          | 0.8837   |
| 0.3376        | 17.85 | 58   | 0.2821          | 0.8837   |
| 0.191         | 18.77 | 61   | 0.2905          | 0.8837   |
| 0.191         | 20.0  | 65   | 0.2616          | 0.8605   |
| 0.191         | 20.92 | 68   | 0.2636          | 0.8837   |
| 0.2065        | 21.85 | 71   | 0.2864          | 0.9070   |
| 0.2065        | 22.77 | 74   | 0.2833          | 0.8605   |
| 0.2065        | 24.0  | 78   | 0.2507          | 0.9070   |
| 0.1328        | 24.92 | 81   | 0.2890          | 0.8837   |
| 0.1328        | 25.85 | 84   | 0.3065          | 0.8837   |
| 0.1328        | 26.77 | 87   | 0.2891          | 0.8837   |
| 0.1065        | 28.0  | 91   | 0.2815          | 0.8837   |
| 0.1065        | 28.92 | 94   | 0.2753          | 0.8837   |
| 0.1065        | 29.85 | 97   | 0.2768          | 0.8837   |
| 0.1122        | 30.77 | 100  | 0.2864          | 0.8837   |
| 0.1122        | 32.0  | 104  | 0.2563          | 0.9070   |
| 0.1122        | 32.92 | 107  | 0.2421          | 0.9302   |
| 0.0879        | 33.85 | 110  | 0.2453          | 0.9070   |
| 0.0879        | 34.77 | 113  | 0.2434          | 0.8837   |
| 0.0879        | 36.0  | 117  | 0.2406          | 0.8837   |
| 0.1082        | 36.92 | 120  | 0.2407          | 0.8837   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1