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This model is a fine-tuned version of OPear/videomae-large-finetuned-UCF-Crime on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.9408 Accuracy: 0.7897
Source du modèle
Description de la source
This model is a fine-tuned version of OPear/videomae-large-finetuned-UCF-Crime on an unknown dataset. It achieves the following results on the evaluation set:
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Sources
1 sourceVérifié 6 août
Artefacts du modèle
1 artefactExtraits de sources
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.1986 | 1.0 | 804 | 0.9949 | 0.7138 |
| 0.4268 | 2.0 | 1608 | 0.9828 | 0.7586 |
| 0.4405 | 3.0 | 2412 | 0.9408 | 0.7897 |
--- library_name: transformers license: cc-by-nc-4.0 base_model: OPear/videomae-large-finetuned-UCF-Crime tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-ucf-crime-balanced 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-ucf-crime-balanced This model is a fine-tuned version of [OPear/videomae-large-finetuned-UCF-Crime](https://huggingface.co/OPear/videomae-large-finetuned-UCF-Crime) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.9408 - Accuracy: 0.7897 ## 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: 1e-05 - train_batch_size: 2 - eval_batch_size: 2 - seed: 42 - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.1986 | 1.0 | 804 | 0.9949 | 0.7138 | | 0.4268 | 2.0 | 1608 | 0.9828 | 0.7586 | | 0.4405 | 3.0 | 2412 | 0.9408 | 0.7897 | ### Framework versions - Transformers 4.57.3 - Pytorch 2.9.0+cu126 - Datasets 4.0.0 - Tokenizers 0.22.1
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo rohithkumarl/videomae-ucf-crime-balanced
