FaceDataset

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: FaceDataset results: [] --- # FaceDataset This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0251 - Accuracy: 0.9909 - Precision: 0.9909 - Recall: 0.9909 - F1: 0.9909 ## 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: 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: 4 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.1021 | 1.0 | 243 | 0.0957 | 0.9781 | 0.9790 | 0.9781 | 0.9780 | | 0.0457 | 2.0 | 486 | 0.0271 | 0.9909 | 0.9910 | 0.9909 | 0.9909 | | 0.0191 | 3.0 | 729 | 0.0414 | 0.9872 | 0.9872 | 0.9872 | 0.9872 | | 0.0082 | 4.0 | 972 | 0.0251 | 0.9909 | 0.9909 | 0.9909 | 0.9909 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2