Violation Classification Bantai Vit V100ep

🚀 violation-classification-bantai-vit-v100ep

This model is a fine - tuned version of google/vit-base-patch16-224-in21k on the image_folder dataset. It can be used for image classification tasks and has achieved good performance on the evaluation set.

🚀 Quick Start

This model is a fine - tuned version of google/vit-base-patch16-224-in21k on the image_folder dataset. It achieves the following results on the evaluation set:

• Loss: 0.2557
• Accuracy: 0.9157

📚 Documentation

Model Information

Model Performance

This model achieves the following results on the evaluation set:

• Loss: 0.2557
• Accuracy: 0.9157

Model Index

• Name: violation - classification - bantai - vit - v100ep Results:
  • Task: Name: Image Classification Type: image - classification Dataset: Name: image_folder Type: image_folder Args: default Metrics:
    • Name: Accuracy Type: accuracy Value: 0.9157343919162757

Training Procedure

Training Hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e - 05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 128
• optimizer: Adam with betas=(0.9,0.999) and epsilon = 1e - 08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 100

Training Results

Framework Versions

• Transformers 4.17.0
• Pytorch 1.10.0+cu111
• Datasets 2.0.0
• Tokenizers 0.11.6

📄 License

This model is licensed under the apache - 2.0 license.