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---
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
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