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videomae-base-finetuned-ucf101-subset
sahild23d23e23re23r/videomae-base-finetuned-ucf101-subset
videomae-base-finetuned-ucf101-subset is a video classification model from sahild23d23e23re23r. 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
- Jan 19, 2024
- Updated
- Feb 18, 2024
- SHA
- 73147ce7
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-ucf101-subset
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: 1.4876
- Accuracy: 0.3623
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 28
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.29 | 8 | 1.5153 | 0.3043 |
| 1.6246 | 1.29 | 16 | 1.4876 | 0.3623 |
| 1.3937 | 2.29 | 24 | 1.4613 | 0.3333 |
| 1.3937 | 3.14 | 28 | 1.4523 | 0.3333 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.14.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Jan 19, 2024
- Updated
- Feb 18, 2024