Videomae Base Finetuned Deception Dataset

🚀 videomae-base-finetuned-deception-dataset

This model is a fine - tuned version of [MCG - NJU/videomae - base](https://huggingface.co/MCG - NJU/videomae - base), which can achieve certain performance on the evaluation set, providing valuable reference for related video analysis tasks.

🚀 Quick Start

This section provides basic information about the model, including its origin and evaluation results. It's a fine - tuned version of [MCG - NJU/videomae - base](https://huggingface.co/MCG - NJU/videomae - base) on an unknown dataset. The evaluation results on the evaluation set are as follows:

• Loss: 1.0893
• Accuracy: 0.7037

📚 Documentation

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: 8
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• 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
• lr_scheduler_warmup_ratio: 0.1
• training_steps: 300

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.1.0+cu121
• Datasets 3.5.0
• Tokenizers 0.21.1

📄 License

This model is licensed under the cc - by - nc - 4.0 license.