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VideoMAEv2-Base-finetuned-ucf101-subset
m21041/VideoMAEv2-Base-finetuned-ucf101-subset
VideoMAEv2-Base-finetuned-ucf101-subset is a machine learning model from m21041. Use it for the machine learning 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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Public
Updated Nov 16, 2025
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At a glance
- Library
- transformers
- License
- cc-by-nc-4.0
- Access
- Public
- Created
- Nov 5, 2025
- Updated
- Nov 16, 2025
- SHA
- 058760c3
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. -->
VideoMAEv2-Base-finetuned-ucf101-subset
This model is a fine-tuned version of OpenGVLab/VideoMAEv2-Base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0314
- Accuracy: 1.0
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: 16
- eval_batch_size: 16
- 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: 72
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9733 | 0.2639 | 19 | 0.4779 | 1.0 |
| 0.1894 | 1.2639 | 38 | 0.0747 | 1.0 |
| 0.0342 | 2.2639 | 57 | 0.0378 | 1.0 |
| 0.0197 | 3.2083 | 72 | 0.0314 | 1.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.0.0
- Tokenizers 0.22.1
- Library
- transformers
- License
- cc-by-nc-4.0
- Created
- Nov 5, 2025
- Updated
- Nov 16, 2025