Videomae Base Finetuned Kinetics Violence Nonviolence Tuned
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0753 Accuracy: 0.9805
Model source
- Kind
- Other
- File size
- 329 MB
- Base model
- MCG-NJU/videomae-base-finetuned-kinetics
- Version
- vRevision 613844b
- Updated
- Sep 18, 2026
- Downloads
- 4.9K
- Source
- Hugging Face
Source description
videomae-base-finetuned-kinetics-violence-nonviolence-tuned
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0753
- Accuracy: 0.9805
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 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: 348
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.074 | 0.2529 | 88 | 0.1186 | 0.9556 |
| 0.0192 | 1.2529 | 176 | 0.0703 | 0.9787 |
| 0.0449 | 2.2529 | 264 | 0.0741 | 0.9787 |
| 0.0061 | 3.2414 | 348 | 0.0753 | 0.9805 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0
Sources
1 source
Sources
1 sourceVerified Sep 18
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
2 excerpts
Source excerpts
2 excerpts--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-kinetics-violence-nonviolence-tuned 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. --> # videomae-base-finetuned-kinetics-violence-nonviolence-tuned This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0753 - Accuracy: 0.9805 ## 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 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: 348 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.074 | 0.2529 | 88 | 0.1186 | 0.9556 | | 0.0192 | 1.2529 | 176 | 0.0703 | 0.9787 | | 0.0449 | 2.2529 | 264 | 0.0741 | 0.9787 | | 0.0061 | 3.2414 | 348 | 0.0753 | 0.9805 | ### Framework versions - Transformers 4.49.0 - Pytorch 2.6.0+cu126 - Datasets 3.3.2 - Tokenizers 0.21.0
Source context: 4938 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo cliffer1/videomae-base-finetuned-kinetics-violence-nonviolence-tuned
