---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: vit_focus_full
  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_full

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0531
- Mse: 0.1291
- Mae: 0.3119

## 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: 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: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Mse    | Mae    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 0.3146        | 0.9855  | 51   | 0.0595          | 0.1403 | 0.3265 |
| 0.2488        | 1.9855  | 102  | 0.0566          | 0.1395 | 0.3253 |
| 0.2278        | 2.9855  | 153  | 0.0611          | 0.1426 | 0.3288 |
| 0.206         | 3.9855  | 204  | 0.0536          | 0.1323 | 0.3180 |
| 0.1902        | 4.9855  | 255  | 0.0619          | 0.1411 | 0.3271 |
| 0.187         | 5.9855  | 306  | 0.0508          | 0.1320 | 0.3169 |
| 0.1757        | 6.9855  | 357  | 0.0537          | 0.1339 | 0.3183 |
| 0.1523        | 7.9855  | 408  | 0.0558          | 0.1330 | 0.3168 |
| 0.1528        | 8.9855  | 459  | 0.0591          | 0.1381 | 0.3225 |
| 0.1416        | 9.9855  | 510  | 0.0536          | 0.1353 | 0.3198 |
| 0.1298        | 10.9855 | 561  | 0.0530          | 0.1325 | 0.3164 |
| 0.1161        | 11.9855 | 612  | 0.0511          | 0.1315 | 0.3156 |
| 0.1085        | 12.9855 | 663  | 0.0531          | 0.1385 | 0.3243 |
| 0.1028        | 13.9855 | 714  | 0.0530          | 0.1316 | 0.3151 |
| 0.0891        | 14.9855 | 765  | 0.0540          | 0.1338 | 0.3178 |
| 0.0878        | 15.9855 | 816  | 0.0536          | 0.1335 | 0.3177 |
| 0.077         | 16.9855 | 867  | 0.0534          | 0.1299 | 0.3132 |
| 0.0769        | 17.9855 | 918  | 0.0549          | 0.1313 | 0.3149 |
| 0.0663        | 18.9855 | 969  | 0.0531          | 0.1291 | 0.3119 |
| 0.064         | 19.9855 | 1020 | 0.0540          | 0.1352 | 0.3197 |
| 0.0608        | 20.9855 | 1071 | 0.0535          | 0.1334 | 0.3179 |
| 0.0548        | 21.9855 | 1122 | 0.0529          | 0.1299 | 0.3134 |
| 0.0517        | 22.9855 | 1173 | 0.0534          | 0.1310 | 0.3152 |
| 0.0498        | 23.9855 | 1224 | 0.0544          | 0.1314 | 0.3151 |
| 0.047         | 24.9855 | 1275 | 0.0531          | 0.1309 | 0.3145 |
| 0.0443        | 25.9855 | 1326 | 0.0537          | 0.1325 | 0.3164 |
| 0.042         | 26.9855 | 1377 | 0.0533          | 0.1319 | 0.3156 |
| 0.0397        | 27.9855 | 1428 | 0.0530          | 0.1317 | 0.3155 |
| 0.0411        | 28.9855 | 1479 | 0.0542          | 0.1328 | 0.3167 |
| 0.0382        | 29.9855 | 1530 | 0.0533          | 0.1327 | 0.3166 |


### Framework versions

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