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---
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
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