Vit Tiny Lfw Faces

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: 8

Training results

Framework versions

• Transformers 5.10.1
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2

--- library_name: transformers license: apache-2.0 base_model: WinKawaks/vit-tiny-patch16-224 tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-tiny-lfw-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-tiny-lfw-faces This model is a fine-tuned version of [WinKawaks/vit-tiny-patch16-224](https://huggingface.co/WinKawaks/vit-tiny-patch16-224) on the None dataset. It achieves the following results on the evaluation set: - Loss: 3.6708 - Accuracy: 0.1759 - F1 Macro: 0.0048 ## 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: 8 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:| | 3.7386 | 1.0 | 142 | 3.6954 | 0.1759 | 0.0048 | | 3.7551 | 2.0 | 284 | 3.6838 | 0.1759 | 0.0048 | | 3.6306 | 3.0 | 426 | 3.6823 | 0.1759 | 0.0048 | | 3.6772 | 4.0 | 568 | 3.6761 | 0.1759 | 0.0048 | | 3.6845 | 5.0 | 710 | 3.6715 | 0.1759 | 0.0048 | | 3.6519 | 6.0 | 852 | 3.6700 | 0.1759 | 0.0048 | | 3.8394 | 7.0 | 994 | 3.6684 | 0.1759 | 0.0048 | | 3.5821 | 8.0 | 1136 | 3.6674 | 0.1759 | 0.0048 | ### Framework versions - Transformers 5.10.1 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2