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videoMAE_kinetics_wlasl2000_coR_20ep
Shawon16/videoMAE_kinetics_wlasl2000_coR_20ep
videoMAE_kinetics_wlasl2000_coR_20ep 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
- Dec 10, 2025
- Updated
- Dec 11, 2025
- SHA
- 05ac5aea
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_kinetics_wlasl2000_coR_20ep
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: 2.4903
- Accuracy: 0.4454
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 |
|---|---|---|---|---|
| 30.4455 | 0.05 | 1786 | 7.5864 | 0.0010 |
| 29.1368 | 1.0500 | 3572 | 6.7872 | 0.0194 |
| 24.787 | 2.0500 | 5358 | 5.8083 | 0.0884 |
| 20.299 | 3.0500 | 7145 | 4.9645 | 0.1619 |
| 16.1178 | 4.05 | 8931 | 4.2633 | 0.2370 |
| 12.3227 | 5.0500 | 10717 | 3.6600 | 0.3029 |
| 9.1282 | 6.0500 | 12503 | 3.2388 | 0.3460 |
| 6.5449 | 7.0500 | 14290 | 2.9354 | 0.3897 |
| 4.6097 | 8.05 | 16076 | 2.7435 | 0.4014 |
| 3.2081 | 9.0500 | 17862 | 2.6247 | 0.4139 |
| 2.2446 | 10.0500 | 19648 | 2.5707 | 0.4247 |
| 1.6181 | 11.0500 | 21435 | 2.4944 | 0.4313 |
| 1.2196 | 12.05 | 23221 | 2.4961 | 0.4318 |
| 0.9689 | 13.0500 | 25007 | 2.4889 | 0.4339 |
| 0.802 | 14.0500 | 26793 | 2.4977 | 0.4408 |
| 0.67 | 15.0500 | 28580 | 2.4818 | 0.4346 |
| 0.5845 | 16.05 | 30366 | 2.4801 | 0.4443 |
| 0.5119 | 17.0500 | 32152 | 2.4924 | 0.4395 |
| 0.4504 | 18.0500 | 33938 | 2.4930 | 0.4454 |
| 0.3911 | 19.0499 | 35720 | 2.4903 | 0.4454 |
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
- Dec 10, 2025
- Updated
- Dec 11, 2025