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videomae-base-finetuned-FT_2PT_3PT
JansherMughal/videomae-base-finetuned-FT_2PT_3PT
videomae-base-finetuned-FT_2PT_3PT is a video classification model from JansherMughal. 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 15, 2025
- Updated
- Nov 15, 2025
- SHA
- 492aa4f5
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-finetuned-FT_2PT_3PT
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: 0.8099
- Accuracy: 0.7290
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: 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: 1320
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9402 | 0.0508 | 67 | 0.9318 | 0.5484 |
| 0.7357 | 1.0508 | 134 | 0.8826 | 0.5871 |
| 0.9663 | 2.0508 | 201 | 0.8852 | 0.5484 |
| 0.6539 | 3.0508 | 268 | 0.7543 | 0.6645 |
| 0.5231 | 4.0508 | 335 | 0.7400 | 0.6323 |
| 0.5684 | 5.0508 | 402 | 1.2109 | 0.6 |
| 0.5058 | 6.0508 | 469 | 1.3525 | 0.5935 |
| 0.3816 | 7.0508 | 536 | 0.7959 | 0.6710 |
| 0.5652 | 8.0508 | 603 | 0.8605 | 0.6581 |
| 0.6047 | 9.0508 | 670 | 0.9432 | 0.6194 |
| 0.4412 | 10.0508 | 737 | 1.0180 | 0.5742 |
| 0.3621 | 11.0508 | 804 | 1.3228 | 0.6065 |
| 0.521 | 12.0508 | 871 | 1.0286 | 0.6258 |
| 0.3356 | 13.0508 | 938 | 1.0859 | 0.6774 |
| 0.3303 | 14.0508 | 1005 | 0.9708 | 0.6710 |
| 0.3837 | 15.0508 | 1072 | 0.9323 | 0.6903 |
| 0.4748 | 16.0508 | 1139 | 0.8099 | 0.7290 |
| 0.3888 | 17.0508 | 1206 | 0.9717 | 0.7161 |
| 0.248 | 18.0508 | 1273 | 0.9719 | 0.6968 |
| 0.4058 | 19.0356 | 1320 | 0.9779 | 0.6968 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Nov 15, 2025
- Updated
- Nov 15, 2025