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VideoMAE_base_wlasl100_20epoch_Signers
Shawon16/VideoMAE_base_wlasl100_20epoch_Signers
VideoMAE_base_wlasl100_20epoch_Signers 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 26, 2025
- Updated
- Nov 26, 2025
- SHA
- f4463558
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_base_wlasl100_20epoch_Signers
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: 3.5389
- Accuracy: 0.1864
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: 3600
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 18.6481 | 0.05 | 180 | 4.6265 | 0.0207 |
| 18.6251 | 1.0499 | 360 | 4.6404 | 0.0266 |
| 18.5402 | 2.0499 | 540 | 4.6303 | 0.0059 |
| 18.3373 | 3.0501 | 721 | 4.6409 | 0.0237 |
| 18.3156 | 4.05 | 901 | 4.6281 | 0.0118 |
| 18.1158 | 5.0499 | 1081 | 4.5800 | 0.0296 |
| 17.8542 | 6.0499 | 1261 | 4.5729 | 0.0237 |
| 17.3491 | 7.0501 | 1442 | 4.4994 | 0.0296 |
| 16.7036 | 8.05 | 1622 | 4.3456 | 0.0355 |
| 15.9584 | 9.0499 | 1802 | 4.2656 | 0.0355 |
| 15.2418 | 10.0499 | 1982 | 4.1895 | 0.0355 |
| 14.3282 | 11.0501 | 2163 | 4.1120 | 0.0562 |
| 13.4384 | 12.05 | 2343 | 4.0232 | 0.0533 |
| 12.3649 | 13.0499 | 2523 | 3.8854 | 0.1006 |
| 11.3044 | 14.0499 | 2703 | 3.7767 | 0.1095 |
| 10.2946 | 15.0501 | 2884 | 3.7317 | 0.1420 |
| 9.5039 | 16.05 | 3064 | 3.6387 | 0.1746 |
| 8.7162 | 17.0499 | 3244 | 3.5911 | 0.1805 |
| 8.1393 | 18.0499 | 3424 | 3.5438 | 0.1982 |
| 7.716 | 19.0487 | 3600 | 3.5389 | 0.1864 |
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 26, 2025
- Updated
- Nov 26, 2025