Vit Motorcycle

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: 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: 10
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 5.9.0
• Pytorch 2.11.0+cu128
• Datasets 4.0.0
• Tokenizers 0.22.2

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-motorcycle 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-motorcycle 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: 1.7219 - Accuracy: 0.2727 ## 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: 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: 10 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.8584 | 1.0 | 3 | 1.7152 | 0.1818 | | 1.7491 | 2.0 | 6 | 1.6670 | 0.2727 | | 1.4504 | 3.0 | 9 | 1.6373 | 0.2727 | | 1.5355 | 4.0 | 12 | 1.6697 | 0.2727 | | 1.4388 | 5.0 | 15 | 1.7158 | 0.2727 | | 1.1518 | 6.0 | 18 | 1.7386 | 0.2727 | | 1.5075 | 7.0 | 21 | 1.7460 | 0.2727 | | 1.5540 | 8.0 | 24 | 1.7286 | 0.2727 | | 1.7147 | 9.0 | 27 | 1.7242 | 0.2727 | | 1.7869 | 10.0 | 30 | 1.7219 | 0.2727 | ### Framework versions - Transformers 5.9.0 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2