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ALL_RGBCROP_Aug16F-8B16F-GWlr-cosine
TanAlexanderlz/ALL_RGBCROP_Aug16F-8B16F-GWlr-cosine
ALL_RGBCROP_Aug16F-8B16F-GWlr-cosine is a video classification model from TanAlexanderlz. 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
- May 28, 2025
- Updated
- May 28, 2025
- SHA
- 3222c85b
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. -->
ALL_RGBCROP_Aug16F-8B16F-GWlr-cosine
This model is a fine-tuned version of MCG-NJU/videomae-base-finetuned-kinetics on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5132
- Accuracy: 0.8483
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 2304
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5085 | 0.0625 | 144 | 0.5645 | 0.7053 |
| 0.2266 | 1.0625 | 288 | 0.5204 | 0.7846 |
| 0.0465 | 2.0625 | 432 | 0.6738 | 0.8191 |
| 0.0075 | 3.0625 | 576 | 0.8976 | 0.8028 |
| 0.0026 | 4.0625 | 720 | 1.0379 | 0.7947 |
| 0.0004 | 5.0625 | 864 | 1.0205 | 0.8110 |
| 0.0003 | 6.0625 | 1008 | 1.1176 | 0.8110 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- May 28, 2025
- Updated
- May 28, 2025