Downloads · 30 days
6
2% of all-time downloads
RALL_RGBCROP_Aug16F-8B16F-lr1
TanAlexanderlz/RALL_RGBCROP_Aug16F-8B16F-lr1
RALL_RGBCROP_Aug16F-8B16F-lr1 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
354
Public
Parameters
86.2M
4.1 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
- May 31, 2025
- Updated
- May 31, 2025
- SHA
- 4957f428
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_Aug16F-8B16F-lr1
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: 0.8799
- Accuracy: 0.8534
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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3462
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3205 | 0.0835 | 289 | 0.4827 | 0.7873 |
| 0.1778 | 1.0835 | 578 | 0.7593 | 0.7955 |
| 0.0017 | 2.0835 | 867 | 0.9236 | 0.7894 |
| 0.0003 | 3.0835 | 1156 | 1.0947 | 0.7935 |
| 0.0003 | 4.0835 | 1445 | 1.1013 | 0.8180 |
| 0.0001 | 5.0835 | 1734 | 1.1582 | 0.8078 |
| 0.0001 | 6.0835 | 2023 | 1.2431 | 0.7996 |
| 0.0001 | 7.0835 | 2312 | 1.1951 | 0.8241 |
| 0.0001 | 8.0835 | 2601 | 1.3349 | 0.7935 |
| 0.0001 | 9.0835 | 2890 | 1.2895 | 0.8078 |
| 0.0001 | 10.0835 | 3179 | 1.3077 | 0.8016 |
| 0.0001 | 11.0817 | 3462 | 1.3116 | 0.8016 |
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 31, 2025
- Updated
- May 31, 2025