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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

KindOtherBase modelMCG-NJU/videomae-base-finetuned-kineticsVersionRevision 613844b

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 LossEpochStepValidation LossAccuracy
0.0740.2529880.11860.9556
0.01921.25291760.07030.9787
0.04492.25292640.07410.9787
0.00613.24143480.07530.9805

Framework versions

  • Transformers 4.49.0
  • Pytorch 2.6.0+cu126
  • Datasets 3.3.2
  • Tokenizers 0.21.0

Sources

1 source

Model artifacts

1 artifact

model.safetensors

safetensors · 329 MB · SHA-256 5166b055ebee…3d53 · Hugging Face

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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