Videomae Base Finetuned Kinetics Finetuned Accident Dataset
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: 0.0077 Accuracy: 1.0
Modellquelle
- Art
- Other
- Dateigröße
- 329 MB
- Basismodell
- MCG-NJU/videomae-base-finetuned-kinetics
- Version
- vRevision 9c24df0
- Aktualisiert
- 24. Okt. 2026
- Downloads
- 14
- Quelle
- Hugging Face
Quellenbeschreibung
videomae-base-finetuned-kinetics-finetuned-Accident-dataset
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: 0.0077
- Accuracy: 1.0
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: 2e-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_ratio: 0.1
- training_steps: 392
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5675 | 0.1276 | 50 | 0.2509 | 0.9126 |
| 0.1471 | 1.1276 | 100 | 0.2354 | 0.9126 |
| 0.022 | 2.1276 | 150 | 0.1293 | 0.9515 |
| 0.0013 | 3.1276 | 200 | 0.0422 | 0.9806 |
| 0.0009 | 4.1276 | 250 | 0.0173 | 0.9903 |
| 0.0024 | 5.1276 | 300 | 0.0544 | 0.9806 |
| 0.0376 | 6.1276 | 350 | 0.0447 | 0.9806 |
| 0.0007 | 7.1071 | 392 | 0.0317 | 0.9806 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1
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-finetuned-kinetics tags: - generated_from_trainer metrics: - accuracy model-index: - name: videomae-base-finetuned-kinetics-finetuned-Accident-dataset 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-Accident-dataset 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: 0.0077 - Accuracy: 1.0 ## 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: 2e-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_ratio: 0.1 - training_steps: 392 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:------:|:----:|:---------------:|:--------:| | 0.5675 | 0.1276 | 50 | 0.2509 | 0.9126 | | 0.1471 | 1.1276 | 100 | 0.2354 | 0.9126 | | 0.022 | 2.1276 | 150 | 0.1293 | 0.9515 | | 0.0013 | 3.1276 | 200 | 0.0422 | 0.9806 | | 0.0009 | 4.1276 | 250 | 0.0173 | 0.9903 | | 0.0024 | 5.1276 | 300 | 0.0544 | 0.9806 | | 0.0376 | 6.1276 | 350 | 0.0447 | 0.9806 | | 0.0007 | 7.1071 | 392 | 0.0317 | 0.9806 | ### Framework versions - Transformers 4.57.1 - Pytorch 2.8.0+cu126 - Datasets 4.4.2 - Tokenizers 0.22.1
Source context: 14 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo esmaelehab/videomae-base-finetuned-kinetics-finetuned-Accident-dataset
Source context: 9 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo esmaelehab/videomae-base-finetuned-kinetics-finetuned-Accident-dataset
