transformers tensorboard safetensors vit image-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
model-index:
- name: ft_outputs_VIT
  results: []
---

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# ft_outputs_VIT

This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4763
- Mse: 0.4763
- Rmse: 0.6901
- Mae: 0.5614

## 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: 8
- eval_batch_size: 8
- seed: 0
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Rmse   | Mae    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 1.5236        | 0.24  | 40   | 0.5961          | 0.5961 | 0.7721 | 0.6121 |
| 0.744         | 0.48  | 80   | 0.5046          | 0.5046 | 0.7104 | 0.5766 |
| 0.7042        | 0.73  | 120  | 0.7303          | 0.7303 | 0.8546 | 0.6874 |
| 0.6464        | 0.97  | 160  | 0.5121          | 0.5121 | 0.7156 | 0.5672 |
| 0.5731        | 1.21  | 200  | 0.5052          | 0.5052 | 0.7108 | 0.5773 |
| 0.5585        | 1.45  | 240  | 0.6825          | 0.6825 | 0.8261 | 0.6646 |
| 0.6561        | 1.7   | 280  | 0.5252          | 0.5252 | 0.7247 | 0.5821 |
| 0.5569        | 1.94  | 320  | 0.5195          | 0.5195 | 0.7207 | 0.5825 |
| 0.5179        | 2.18  | 360  | 0.4983          | 0.4983 | 0.7059 | 0.5691 |
| 0.5308        | 2.42  | 400  | 0.5014          | 0.5014 | 0.7081 | 0.5678 |
| 0.5462        | 2.67  | 440  | 0.4963          | 0.4963 | 0.7045 | 0.5705 |
| 0.5499        | 2.91  | 480  | 0.4772          | 0.4772 | 0.6908 | 0.5621 |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.3.2
- Tokenizers 0.15.2
