---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reapikui_best_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# reapikui_best_model

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: 0.8426
- Accuracy: 0.922

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.8526        | 0.992 | 62   | 2.6167          | 0.836    |
| 1.7104        | 2.0   | 125  | 1.5818          | 0.884    |
| 1.2318        | 2.992 | 187  | 1.1876          | 0.915    |
| 0.9759        | 4.0   | 250  | 0.9661          | 0.92     |
| 0.8262        | 4.992 | 312  | 0.8780          | 0.92     |
| 0.7681        | 5.952 | 372  | 0.8362          | 0.93     |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1