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videomae-base-finetuned-gemep-epochs25
KG5KEY/videomae-base-finetuned-gemep-epochs25
videomae-base-finetuned-gemep-epochs25 is a video classification model from KG5KEY. 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
- Feb 28, 2024
- Updated
- Feb 28, 2024
- SHA
- cb2b03e4
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-gemep-epochs25
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: 0.4373
- Accuracy: 0.9123
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: 1350
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.7648 | 0.04 | 54 | 1.7458 | 0.2698 |
| 1.6977 | 1.04 | 108 | 1.5724 | 0.2698 |
| 1.5208 | 2.04 | 162 | 1.5350 | 0.2857 |
| 1.39 | 3.04 | 216 | 1.4793 | 0.4286 |
| 1.3546 | 4.04 | 270 | 1.7122 | 0.2857 |
| 0.9587 | 5.04 | 324 | 1.4137 | 0.3492 |
| 1.0259 | 6.04 | 378 | 1.2302 | 0.6190 |
| 0.7292 | 7.04 | 432 | 1.4772 | 0.3810 |
| 0.6499 | 8.04 | 486 | 1.0864 | 0.5873 |
| 0.5417 | 9.04 | 540 | 1.4085 | 0.4603 |
| 0.5073 | 10.04 | 594 | 1.5436 | 0.5556 |
| 0.5052 | 11.04 | 648 | 1.2583 | 0.6190 |
| 0.419 | 12.04 | 702 | 1.1921 | 0.6349 |
| 0.2677 | 13.04 | 756 | 1.0662 | 0.6825 |
| 0.1601 | 14.04 | 810 | 0.7688 | 0.7143 |
| 0.1784 | 15.04 | 864 | 1.2971 | 0.6508 |
| 0.1338 | 16.04 | 918 | 0.9488 | 0.7937 |
| 0.0875 | 17.04 | 972 | 1.0488 | 0.7619 |
| 0.0748 | 18.04 | 1026 | 0.9617 | 0.8095 |
| 0.0973 | 19.04 | 1080 | 1.0684 | 0.7460 |
| 0.0443 | 20.04 | 1134 | 1.0433 | 0.7778 |
| 0.0787 | 21.04 | 1188 | 0.8444 | 0.8254 |
| 0.0035 | 22.04 | 1242 | 1.1333 | 0.7778 |
| 0.0033 | 23.04 | 1296 | 0.9644 | 0.8095 |
| 0.0686 | 24.04 | 1350 | 0.9196 | 0.8254 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Feb 28, 2024
- Updated
- Feb 28, 2024