| --- |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - HHD |
| - 3_class |
| - ViT |
| - generated_from_trainer |
| model-index: |
| - name: ViT_face |
| 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_face |
| |
| This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the face dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6941 |
| |
| ## 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: 2e-05 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 30 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | No log | 1.0 | 10 | 1.0691 | |
| | No log | 2.0 | 20 | 1.0378 | |
| | No log | 3.0 | 30 | 0.9958 | |
| | No log | 4.0 | 40 | 0.9437 | |
| | No log | 5.0 | 50 | 0.8915 | |
| | No log | 6.0 | 60 | 0.8396 | |
| | No log | 7.0 | 70 | 0.7950 | |
| | No log | 8.0 | 80 | 0.7602 | |
| | No log | 9.0 | 90 | 0.7246 | |
| | No log | 10.0 | 100 | 0.7009 | |
| | No log | 11.0 | 110 | 0.6882 | |
| | No log | 12.0 | 120 | 0.6700 | |
| | No log | 13.0 | 130 | 0.6629 | |
| | No log | 14.0 | 140 | 0.6646 | |
| | No log | 15.0 | 150 | 0.6558 | |
| | No log | 16.0 | 160 | 0.6679 | |
| | No log | 17.0 | 170 | 0.6637 | |
| | No log | 18.0 | 180 | 0.6689 | |
| | No log | 19.0 | 190 | 0.6690 | |
| | No log | 20.0 | 200 | 0.6744 | |
| | No log | 21.0 | 210 | 0.6787 | |
| | No log | 22.0 | 220 | 0.6823 | |
| | No log | 23.0 | 230 | 0.6832 | |
| | No log | 24.0 | 240 | 0.6866 | |
| | No log | 25.0 | 250 | 0.6883 | |
| | No log | 26.0 | 260 | 0.6912 | |
| | No log | 27.0 | 270 | 0.6923 | |
| | No log | 28.0 | 280 | 0.6935 | |
| | No log | 29.0 | 290 | 0.6939 | |
| | No log | 30.0 | 300 | 0.6941 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.4 |
| - Pytorch 2.4.0+cu121 |
| - Datasets 2.21.0 |
| - Tokenizers 0.19.1 |
| |
