---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-vit
  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. -->

# test-vit

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4068
- Accuracy: 0.9909

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 11

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.84  | 4    | 1.3347          | 0.9027   |
| No log        | 1.89  | 9    | 1.0340          | 0.9605   |
| 1.2661        | 2.95  | 14   | 0.8152          | 0.9696   |
| 1.2661        | 4.0   | 19   | 0.6598          | 0.9878   |
| 0.7865        | 4.84  | 23   | 0.5723          | 0.9878   |
| 0.7865        | 5.89  | 28   | 0.4964          | 0.9909   |
| 0.5287        | 6.95  | 33   | 0.4474          | 0.9909   |
| 0.5287        | 8.0   | 38   | 0.4200          | 0.9939   |
| 0.4142        | 8.84  | 42   | 0.4085          | 0.9909   |
| 0.4142        | 9.26  | 44   | 0.4068          | 0.9909   |


### Framework versions

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