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RALL_RGBCROP_ori16F-8B16F-GACWDlr
TanAlexanderlz/RALL_RGBCROP_ori16F-8B16F-GACWDlr
RALL_RGBCROP_ori16F-8B16F-GACWDlr 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 29, 2025
- Updated
- May 29, 2025
- SHA
- ca7593ba
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. -->
RALL_RGBCROP_ori16F-8B16F-GACWDlr
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: 0.5287
- Accuracy: 0.8434
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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 768
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6817 | 0.0625 | 48 | 0.6756 | 0.5706 |
| 0.5221 | 1.0625 | 96 | 0.6408 | 0.6503 |
| 0.3066 | 2.0625 | 144 | 0.5166 | 0.7607 |
| 0.1279 | 3.0625 | 192 | 0.4812 | 0.7669 |
| 0.1039 | 4.0625 | 240 | 0.5521 | 0.7914 |
| 0.0373 | 5.0625 | 288 | 0.5742 | 0.7914 |
| 0.0071 | 6.0625 | 336 | 0.6844 | 0.7975 |
| 0.0035 | 7.0625 | 384 | 0.7469 | 0.7975 |
| 0.0034 | 8.0625 | 432 | 0.8036 | 0.7975 |
| 0.0015 | 9.0625 | 480 | 0.8369 | 0.8098 |
| 0.0012 | 10.0625 | 528 | 0.8380 | 0.8037 |
| 0.0011 | 11.0625 | 576 | 0.8600 | 0.7975 |
| 0.0009 | 12.0625 | 624 | 0.8795 | 0.8037 |
| 0.0009 | 13.0625 | 672 | 0.8881 | 0.7975 |
| 0.0009 | 14.0625 | 720 | 0.8948 | 0.7975 |
Framework versions
- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- May 29, 2025
- Updated
- May 29, 2025