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videomae-base-finetuned-good-gesturePhaseV3
alexgrigore/videomae-base-finetuned-good-gesturePhaseV3
videomae-base-finetuned-good-gesturePhaseV3 is a video classification model from alexgrigore. 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
- Jun 8, 2024
- Updated
- Jun 8, 2024
- SHA
- b66819a6
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-good-gesturePhaseV3
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:
- Accuracy: 0.6939
- Loss: 0.9297
- Accuracy Hold: 0.0
- Accuracy Stroke: 0.0
- Accuracy Recovery: 0.0
- Accuracy Preparation: 0.8961
- Accuracy Unknown: 0.9429
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: 1e-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: 690
Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss | Accuracy Hold | Accuracy Stroke | Accuracy Recovery | Accuracy Preparation | Accuracy Unknown |
|---|---|---|---|---|---|---|---|---|---|
| 1.0859 | 0.1014 | 70 | 0.5597 | 1.2821 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 1.1816 | 1.1014 | 140 | 0.5597 | 1.2569 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 0.9776 | 2.1014 | 210 | 0.5597 | 1.1835 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0 |
| 0.9867 | 3.1014 | 280 | 0.6119 | 1.0721 | 0.0 | 0.0 | 0.0 | 0.96 | 0.3846 |
| 1.0732 | 4.1014 | 350 | 0.6045 | 1.1086 | 0.0 | 0.0 | 0.0 | 0.7333 | 1.0 |
| 0.9688 | 5.1014 | 420 | 0.6866 | 0.9288 | 0.0 | 0.0 | 0.0 | 0.9333 | 0.8462 |
| 0.7733 | 6.1014 | 490 | 0.6567 | 0.9749 | 0.0 | 0.0 | 0.0 | 0.8267 | 1.0 |
| 0.8798 | 7.1014 | 560 | 0.6866 | 0.8742 | 0.0 | 0.0 | 0.0 | 0.92 | 0.8846 |
| 0.7771 | 8.1014 | 630 | 0.7015 | 0.8452 | 0.0 | 0.0 | 0.0 | 0.92 | 0.9615 |
| 1.0448 | 9.0870 | 690 | 0.7239 | 0.8357 | 0.0 | 0.0 | 0.0 | 0.96 | 0.9615 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Jun 8, 2024
- Updated
- Jun 8, 2024