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VideoMAE_wlasl_2000_20_epochs
Shawon16/VideoMAE_wlasl_2000_20_epochs
VideoMAE_wlasl_2000_20_epochs is a video classification model from Shawon16. Use it for the video classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Video Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- videomae
- Access
- Public
- Created
- Nov 12, 2025
- Updated
- Nov 13, 2025
- SHA
- e8d4f8cb
Base models
Model card
From the Hugging Face model README
<!-- 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_wlasl_2000_20_epochs
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: 2.4885
- Accuracy: 0.4484
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Use 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: 35720
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 30.4463 | 0.05 | 1786 | 7.5937 | 0.0008 |
| 29.0015 | 1.0500 | 3572 | 6.7471 | 0.0209 |
| 24.748 | 2.0500 | 5358 | 5.8146 | 0.0855 |
| 20.3678 | 3.0500 | 7145 | 4.9957 | 0.1599 |
| 16.2208 | 4.05 | 8931 | 4.2713 | 0.2326 |
| 12.4666 | 5.0500 | 10717 | 3.7028 | 0.3018 |
| 9.2225 | 6.0500 | 12503 | 3.2447 | 0.3547 |
| 6.6389 | 7.0500 | 14290 | 2.9646 | 0.3820 |
| 4.7134 | 8.05 | 16076 | 2.7632 | 0.4027 |
| 3.2725 | 9.0500 | 17862 | 2.6250 | 0.4203 |
| 2.309 | 10.0500 | 19648 | 2.5632 | 0.4175 |
| 1.677 | 11.0500 | 21435 | 2.5348 | 0.4206 |
| 1.2664 | 12.05 | 23221 | 2.4956 | 0.4300 |
| 1.0 | 13.0500 | 25007 | 2.4907 | 0.4262 |
| 0.8149 | 14.0500 | 26793 | 2.4883 | 0.4354 |
| 0.6907 | 15.0500 | 28580 | 2.4774 | 0.4428 |
| 0.5841 | 16.05 | 30366 | 2.4884 | 0.4428 |
| 0.533 | 17.0500 | 32152 | 2.4878 | 0.4469 |
| 0.4575 | 18.0500 | 33938 | 2.4865 | 0.4469 |
| 0.3969 | 19.0499 | 35720 | 2.4885 | 0.4484 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Nov 12, 2025
- Updated
- Nov 13, 2025