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videomae-base-finetuned-basketball-subset-20epochs
yerx/videomae-base-finetuned-basketball-subset-20epochs
videomae-base-finetuned-basketball-subset-20epochs is a video classification model from yerx. 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
- Apr 26, 2023
- Updated
- Apr 26, 2023
- SHA
- fa71f761
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-basketball-subset-20epochs
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: 2.8785
- Accuracy: 0.1972
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: 1
- eval_batch_size: 1
- 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: 4060
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.2525 | 0.05 | 200 | 0.7720 | 0.52 |
| 0.8649 | 1.05 | 400 | 0.7721 | 0.48 |
| 1.0703 | 2.05 | 600 | 1.3605 | 0.52 |
| 0.606 | 3.05 | 800 | 1.0668 | 0.6 |
| 2.0221 | 4.05 | 1000 | 1.1741 | 0.56 |
| 1.2916 | 5.05 | 1200 | 1.4747 | 0.52 |
| 1.4861 | 6.05 | 1400 | 1.1454 | 0.6 |
| 1.3012 | 7.05 | 1600 | 1.6105 | 0.56 |
| 1.3327 | 8.05 | 1800 | 1.2343 | 0.52 |
| 2.077 | 9.05 | 2000 | 1.3243 | 0.6 |
| 1.2349 | 10.05 | 2200 | 1.2044 | 0.6 |
| 1.005 | 11.05 | 2400 | 1.6417 | 0.52 |
| 1.1622 | 12.05 | 2600 | 1.3058 | 0.56 |
| 0.8031 | 13.05 | 2800 | 0.6776 | 0.48 |
| 0.8588 | 14.05 | 3000 | 1.1644 | 0.64 |
| 0.8451 | 15.05 | 3200 | 0.8491 | 0.64 |
| 1.1336 | 16.05 | 3400 | 1.0237 | 0.6 |
| 1.5719 | 17.05 | 3600 | 1.0391 | 0.64 |
| 0.4892 | 18.05 | 3800 | 0.9995 | 0.64 |
| 1.2092 | 19.05 | 4000 | 0.9802 | 0.56 |
| 0.9784 | 20.01 | 4060 | 0.9771 | 0.56 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Apr 26, 2023
- Updated
- Apr 26, 2023