Videomae Base Finetuned Ucf101 Subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.5207 Model Preparation Time: 0.0029 Accuracy: 0.8
Modellquelle
- Art
- Other
- Dateigröße
- 329 MB
- Basismodell
- MCG-NJU/videomae-base
- Version
- vRevision 022ea66
- Aktualisiert
- 24. Okt. 2026
- Downloads
- 3
- Quelle
- Hugging Face
Quellenbeschreibung
videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5207
- Model Preparation Time: 0.0029
- Accuracy: 0.8
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_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_steps: 0.1
- training_steps: 148
Training results
| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy |
|---|---|---|---|---|---|
| 2.1604 | 0.2568 | 38 | 1.8775 | 0.0029 | 0.3429 |
| 0.9866 | 1.2568 | 76 | 0.9540 | 0.0029 | 0.7429 |
| 0.4887 | 2.2568 | 114 | 0.6650 | 0.0029 | 0.7 |
| 0.3097 | 3.2297 | 148 | 0.4687 | 0.0029 | 0.8429 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Quellen
1 Quelle
Quellen
1 QuelleVerifiziert 24. Okt.
Modellartefakte
1 Artefakt
Modellartefakte
1 ArtefaktQuellenauszüge
3 Auszüge
Quellenauszüge
3 Auszüge--- library_name: transformers license: cc-by-nc-4.0 base_model: MCG-NJU/videomae-base tags: - generated_from_trainer metrics: - accuracy 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. It achieves the following results on the evaluation set: - Loss: 0.5207 - Model Preparation Time: 0.0029 - Accuracy: 0.8 ## 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_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_steps: 0.1 - training_steps: 148 ### Training results | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Accuracy | |:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:| | 2.1604 | 0.2568 | 38 | 1.8775 | 0.0029 | 0.3429 | | 0.9866 | 1.2568 | 76 | 0.9540 | 0.0029 | 0.7429 | | 0.4887 | 2.2568 | 114 | 0.6650 | 0.0029 | 0.7 | | 0.3097 | 3.2297 | 148 | 0.4687 | 0.0029 | 0.8429 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 3 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo dd00697/videomae-base-finetuned-ucf101-subset
Source context: 4 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo dd00697/videomae-base-finetuned-ucf101-subset
