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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
Source du modèle
Description de la source
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:
More information needed
Sources
1 sourceVérifié 18 sept.
Artefacts du modèle
1 artefactExtraits de sources
2 extraitsMore information needed
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The following hyperparameters were used during training:
| 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 |
--- 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
