---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: vit_focus
  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_focus

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: 0.0599
- Mse: 0.1695
- Mae: 0.3672

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mse    | Mae    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 2    | 0.1236          | 0.2098 | 0.4114 |
| No log        | 2.0   | 4    | 0.1196          | 0.2083 | 0.4100 |
| No log        | 3.0   | 6    | 0.1133          | 0.2058 | 0.4075 |
| No log        | 4.0   | 8    | 0.1060          | 0.2028 | 0.4042 |
| No log        | 5.0   | 10   | 0.1033          | 0.2020 | 0.4024 |
| No log        | 6.0   | 12   | 0.0938          | 0.1972 | 0.3968 |
| No log        | 7.0   | 14   | 0.1082          | 0.2021 | 0.4018 |
| No log        | 8.0   | 16   | 0.0798          | 0.1897 | 0.3890 |
| No log        | 9.0   | 18   | 0.1011          | 0.1983 | 0.3964 |
| No log        | 10.0  | 20   | 0.0874          | 0.1913 | 0.3888 |
| No log        | 11.0  | 22   | 0.0687          | 0.1811 | 0.3799 |
| No log        | 12.0  | 24   | 0.0812          | 0.1892 | 0.3876 |
| No log        | 13.0  | 26   | 0.0704          | 0.1831 | 0.3812 |
| No log        | 14.0  | 28   | 0.0579          | 0.1744 | 0.3713 |
| No log        | 15.0  | 30   | 0.0678          | 0.1791 | 0.3762 |
| No log        | 16.0  | 32   | 0.0881          | 0.1883 | 0.3863 |
| No log        | 17.0  | 34   | 0.0960          | 0.1896 | 0.3880 |
| No log        | 18.0  | 36   | 0.0696          | 0.1776 | 0.3753 |
| No log        | 19.0  | 38   | 0.0576          | 0.1716 | 0.3692 |
| No log        | 20.0  | 40   | 0.0585          | 0.1720 | 0.3697 |
| No log        | 21.0  | 42   | 0.0710          | 0.1792 | 0.3773 |
| No log        | 22.0  | 44   | 0.0815          | 0.1843 | 0.3829 |
| No log        | 23.0  | 46   | 0.0686          | 0.1737 | 0.3710 |
| No log        | 24.0  | 48   | 0.0674          | 0.1734 | 0.3704 |
| 0.118         | 25.0  | 50   | 0.0707          | 0.1776 | 0.3757 |
| 0.118         | 26.0  | 52   | 0.0753          | 0.1817 | 0.3804 |
| 0.118         | 27.0  | 54   | 0.0708          | 0.1787 | 0.3771 |
| 0.118         | 28.0  | 56   | 0.0637          | 0.1721 | 0.3699 |
| 0.118         | 29.0  | 58   | 0.0599          | 0.1695 | 0.3672 |
| 0.118         | 30.0  | 60   | 0.0627          | 0.1731 | 0.3711 |
| 0.118         | 31.0  | 62   | 0.0693          | 0.1786 | 0.3770 |
| 0.118         | 32.0  | 64   | 0.0738          | 0.1799 | 0.3781 |
| 0.118         | 33.0  | 66   | 0.0730          | 0.1773 | 0.3752 |
| 0.118         | 34.0  | 68   | 0.0684          | 0.1735 | 0.3711 |
| 0.118         | 35.0  | 70   | 0.0642          | 0.1702 | 0.3673 |
| 0.118         | 36.0  | 72   | 0.0641          | 0.1721 | 0.3694 |
| 0.118         | 37.0  | 74   | 0.0687          | 0.1758 | 0.3737 |
| 0.118         | 38.0  | 76   | 0.0739          | 0.1788 | 0.3772 |
| 0.118         | 39.0  | 78   | 0.0706          | 0.1765 | 0.3748 |
| 0.118         | 40.0  | 80   | 0.0665          | 0.1726 | 0.3704 |
| 0.118         | 41.0  | 82   | 0.0642          | 0.1703 | 0.3677 |
| 0.118         | 42.0  | 84   | 0.0659          | 0.1719 | 0.3695 |
| 0.118         | 43.0  | 86   | 0.0682          | 0.1743 | 0.3721 |
| 0.118         | 44.0  | 88   | 0.0723          | 0.1776 | 0.3759 |
| 0.118         | 45.0  | 90   | 0.0730          | 0.1778 | 0.3761 |
| 0.118         | 46.0  | 92   | 0.0738          | 0.1775 | 0.3757 |
| 0.118         | 47.0  | 94   | 0.0743          | 0.1770 | 0.3751 |
| 0.118         | 48.0  | 96   | 0.0743          | 0.1766 | 0.3747 |
| 0.118         | 49.0  | 98   | 0.0737          | 0.1764 | 0.3746 |
| 0.0449        | 50.0  | 100  | 0.0729          | 0.1760 | 0.3741 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0
- Datasets 3.5.1
- Tokenizers 0.21.1