---
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 the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0604
- Mse: 0.1248
- Mae: 0.3083

## 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    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| No log        | 1.0     | 25   | 0.0685          | 0.1397 | 0.3276 |
| 0.2799        | 2.0     | 50   | 0.0614          | 0.1327 | 0.3184 |
| 0.2799        | 3.0     | 75   | 0.0575          | 0.1317 | 0.3171 |
| 0.2134        | 4.0     | 100  | 0.0683          | 0.1370 | 0.3236 |
| 0.2018        | 5.0     | 125  | 0.0610          | 0.1353 | 0.3213 |
| 0.2018        | 6.0     | 150  | 0.0596          | 0.1295 | 0.3133 |
| 0.1714        | 7.0     | 175  | 0.0588          | 0.1327 | 0.3186 |
| 0.1589        | 8.0     | 200  | 0.0621          | 0.1348 | 0.3204 |
| 0.1589        | 9.0     | 225  | 0.0615          | 0.1306 | 0.3157 |
| 0.1381        | 10.0    | 250  | 0.0557          | 0.1280 | 0.3118 |
| 0.1381        | 11.0    | 275  | 0.0580          | 0.1311 | 0.3158 |
| 0.1229        | 12.0    | 300  | 0.0563          | 0.1294 | 0.3139 |
| 0.1112        | 13.0    | 325  | 0.0629          | 0.1393 | 0.3253 |
| 0.1112        | 14.0    | 350  | 0.0605          | 0.1290 | 0.3128 |
| 0.0999        | 15.0    | 375  | 0.0604          | 0.1248 | 0.3083 |
| 0.0896        | 16.0    | 400  | 0.0556          | 0.1308 | 0.3153 |
| 0.0896        | 17.0    | 425  | 0.0610          | 0.1347 | 0.3201 |
| 0.0776        | 18.0    | 450  | 0.0574          | 0.1259 | 0.3093 |
| 0.0776        | 19.0    | 475  | 0.0584          | 0.1253 | 0.3085 |
| 0.069         | 20.0    | 500  | 0.0595          | 0.1265 | 0.3097 |
| 0.0649        | 21.0    | 525  | 0.0576          | 0.1308 | 0.3150 |
| 0.0649        | 22.0    | 550  | 0.0574          | 0.1274 | 0.3109 |
| 0.056         | 23.0    | 575  | 0.0578          | 0.1307 | 0.3149 |
| 0.0508        | 24.0    | 600  | 0.0563          | 0.1296 | 0.3139 |
| 0.0508        | 25.0    | 625  | 0.0568          | 0.1312 | 0.3157 |
| 0.0468        | 26.0    | 650  | 0.0578          | 0.1287 | 0.3123 |
| 0.0468        | 27.0    | 675  | 0.0579          | 0.1305 | 0.3147 |
| 0.0432        | 28.0    | 700  | 0.0572          | 0.1301 | 0.3143 |
| 0.0419        | 28.8247 | 720  | 0.0580          | 0.1308 | 0.3150 |


### Framework versions

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