|
|
--- |
|
|
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 |
|
|
|
