| --- |
| library_name: transformers |
| base_model: mo-thecreator/vit-Facial-Expression-Recognition |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: vit-facial-expression-fatigue |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: default |
| split: train |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9363636363636364 |
| --- |
| |
| <!-- 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-facial-expression-fatigue |
|
|
| This model is a fine-tuned version of [mo-thecreator/vit-Facial-Expression-Recognition](https://huggingface.co/mo-thecreator/vit-Facial-Expression-Recognition) on the imagefolder dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3145 |
| - Accuracy: 0.9364 |
|
|
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 100 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.2255 | 1.0 | 110 | 0.1784 | 0.9409 | |
| | 0.0959 | 2.0 | 220 | 0.2311 | 0.9364 | |
| | 0.0372 | 3.0 | 330 | 0.2092 | 0.9409 | |
| | 0.0056 | 4.0 | 440 | 0.3145 | 0.9364 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.6.2 |
| - Pytorch 2.9.1 |
| - Datasets 4.8.4 |
| - Tokenizers 0.22.2 |
| |
