Videomae Base Finetuned Ucf101 Subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
Source du modèle
- Type
- Other
- Taille du fichier
- 329 MB
- Modèle de base
- MCG-NJU/videomae-base
- Version
- vRevision 62e2e61
- Mis à jour
- 18 sept. 2026
- Téléchargements
- 3
- Source
- Hugging Face
Description de la source
videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset.
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
- 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: 148
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu118
- Datasets 3.3.0
- Tokenizers 0.21.0
Sources
1 source
Sources
1 sourceVérifié 18 sept.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
2 extraits
Extraits de sources
2 extraits--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer model-index: - name: videomae-base-finetuned-ucf101-subset 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-ucf101-subset This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset. ## 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 - 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: 148 ### Framework versions - Transformers 4.48.3 - Pytorch 2.6.0+cu118 - Datasets 3.3.0 - Tokenizers 0.21.0
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo fhuseravip/videomae-base-finetuned-ucf101-subset
