Videomae Base Finetuned Kinetics Finetuned
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: 0.5397 Accuracy: 0.8356
Model source
- Kind
- Other
- File size
- 329 MB
- Base model
- MCG-NJU/videomae-base-finetuned-kinetics
- Version
- vRevision 1f724f8
- Updated
- Oct 10, 2026
- Downloads
- 7
- Source
- Hugging Face
Source description
videomae-base-finetuned-kinetics-finetuned
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: 0.5397
- Accuracy: 0.8356
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: 240
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5826 | 0.2542 | 61 | 0.7650 | 0.7807 |
| 0.3585 | 1.2542 | 122 | 0.6335 | 0.7719 |
| 0.1913 | 2.2542 | 183 | 0.6832 | 0.7895 |
| 0.0991 | 3.2375 | 240 | 0.7484 | 0.7632 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.1+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVerified Oct 10
Model artifacts
1 artifact
Model artifacts
1 artifactSource excerpts
3 excerpts
Source excerpts
3 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-finetuned 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-finetuned 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: 0.5397 - Accuracy: 0.8356 ## 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: 240 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.5826 | 0.2542 | 61 | 0.7650 | 0.7807 | | 0.3585 | 1.2542 | 122 | 0.6335 | 0.7719 | | 0.1913 | 2.2542 | 183 | 0.6832 | 0.7895 | | 0.0991 | 3.2375 | 240 | 0.7484 | 0.7632 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.12.1+cu130 - Datasets 5.0.0 - Tokenizers 0.22.2
Source context: 7 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo thenextme/videomae-base-finetuned-kinetics-finetuned
Source context: 60 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo thenextme/videomae-base-finetuned-kinetics-finetuned
