| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - image-classification |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: vit-cropped-faces |
| | 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-cropped-faces |
| |
|
| | 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 emigomez/vit-cropped-faces dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0109 |
| | - Accuracy: 1.0 |
| |
|
| | ## 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: 0.0002 |
| | - train_batch_size: 16 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - 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: 20 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 0.0254 | 3.125 | 100 | 0.0136 | 1.0 | |
| | | 0.0053 | 6.25 | 200 | 0.0109 | 1.0 | |
| | | 0.0033 | 9.375 | 300 | 0.0139 | 1.0 | |
| | | 0.0025 | 12.5 | 400 | 0.0128 | 1.0 | |
| | | 0.0021 | 15.625 | 500 | 0.0122 | 1.0 | |
| | | 0.0019 | 18.75 | 600 | 0.0120 | 1.0 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.48.3 |
| | - Pytorch 2.5.1+cu124 |
| | - Datasets 3.3.2 |
| | - Tokenizers 0.21.0 |
| |
|
