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VideoMAE_kinetics_wlasl100_20epoch_Signers
Shawon16/VideoMAE_kinetics_wlasl100_20epoch_Signers
VideoMAE_kinetics_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
- 2a5a1f18
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_wlasl100_20epoch_Signers
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: 0.9211
- Accuracy: 0.7692
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 |
|---|---|---|---|---|
| 18.4524 | 0.05 | 180 | 4.5268 | 0.0325 |
| 16.7504 | 1.0499 | 360 | 3.6888 | 0.1864 |
| 12.2073 | 2.0499 | 540 | 2.8001 | 0.4675 |
| 8.0525 | 3.0501 | 721 | 2.1476 | 0.6006 |
| 5.2821 | 4.05 | 901 | 1.7964 | 0.6450 |
| 3.2722 | 5.0499 | 1081 | 1.4956 | 0.7041 |
| 2.0177 | 6.0499 | 1261 | 1.3690 | 0.6746 |
| 1.2351 | 7.0501 | 1442 | 1.2708 | 0.6923 |
| 0.7437 | 8.05 | 1622 | 1.1608 | 0.7160 |
| 0.4375 | 9.0499 | 1802 | 1.0340 | 0.7515 |
| 0.2713 | 10.0499 | 1982 | 1.1279 | 0.7041 |
| 0.1569 | 11.0501 | 2163 | 0.9909 | 0.7367 |
| 0.1114 | 12.05 | 2343 | 0.9958 | 0.7456 |
| 0.074 | 13.0499 | 2523 | 0.9627 | 0.7485 |
| 0.0588 | 14.0499 | 2703 | 0.9344 | 0.7604 |
| 0.0579 | 15.0501 | 2884 | 0.9531 | 0.7663 |
| 0.0511 | 16.05 | 3064 | 0.9183 | 0.7663 |
| 0.0456 | 17.0499 | 3244 | 0.9359 | 0.7663 |
| 0.0399 | 18.0499 | 3424 | 0.9284 | 0.7633 |
| 0.0429 | 19.0487 | 3600 | 0.9211 | 0.7692 |
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