Downloads · 30 days
4
3% of all-time downloads
BxSD-finetuned-UCF_RGBCROP_5e6-poly_2
TanAlexanderlz/BxSD-finetuned-UCF_RGBCROP_5e6-poly_2
BxSD-finetuned-UCF_RGBCROP_5e6-poly_2 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. --
All-time downloads
131
Public
Parameters
86.2M
5.2 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors345 MB · 100%
At a glance
- Task
- Video Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- videomae
- Access
- Public
- Created
- Jun 2, 2025
- Updated
- Jun 2, 2025
- SHA
- 9e990e4c
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. -->
BxSD-finetuned-UCF_RGBCROP_5e6-poly_2
This model is a fine-tuned version of TanAlexanderlz/BxSD_RGBCROP_Aug16F-8B16F5e6-poly on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3358
- Accuracy: 0.8056
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 345
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5386 | 0.0696 | 24 | 0.5426 | 0.7619 |
| 0.284 | 1.0696 | 48 | 0.4675 | 0.8333 |
| 0.0153 | 2.0696 | 72 | 0.3591 | 0.9048 |
| 0.0033 | 3.0696 | 96 | 0.4866 | 0.9048 |
| 0.0014 | 4.0696 | 120 | 0.4560 | 0.9048 |
| 0.0011 | 5.0696 | 144 | 0.4384 | 0.9286 |
| 0.0009 | 6.0696 | 168 | 0.4652 | 0.9286 |
| 0.0008 | 7.0696 | 192 | 0.4820 | 0.9286 |
| 0.0007 | 8.0696 | 216 | 0.4606 | 0.9286 |
| 0.0006 | 9.0696 | 240 | 0.4676 | 0.9286 |
| 0.0006 | 10.0696 | 264 | 0.4681 | 0.9286 |
| 0.0006 | 11.0696 | 288 | 0.4760 | 0.9286 |
| 0.0005 | 12.0696 | 312 | 0.4777 | 0.9286 |
| 0.0005 | 13.0696 | 336 | 0.4788 | 0.9286 |
| 0.0006 | 14.0261 | 345 | 0.4786 | 0.9286 |
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
- Jun 2, 2025
- Updated
- Jun 2, 2025