---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ft_stable_diffusion
  results: []
---

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

This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the generated by stable diffusion dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3650
- Accuracy: 0.9194

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 70   | 0.9239          | 0.7705   |
| 1.1759        | 2.0   | 140  | 0.5778          | 0.8852   |
| 0.5081        | 3.0   | 210  | 0.4438          | 0.9180   |
| 0.5081        | 4.0   | 280  | 0.3857          | 0.9344   |
| 0.3442        | 5.0   | 350  | 0.3700          | 0.9344   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3