Downloads · 30 days
1
1% of all-time downloads
ALL_RGBCROP_ori16F-8B16F-GACWDlr5e-6
TanAlexanderlz/ALL_RGBCROP_ori16F-8B16F-GACWDlr5e-6
ALL_RGBCROP_ori16F-8B16F-GACWDlr5e-6 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
84
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
- May 28, 2025
- Updated
- May 28, 2025
- SHA
- 49b902c5
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_ori16F-8B16F-GACWDlr5e-6
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: 0.4757
- Accuracy: 0.8443
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-06
- 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 |
|---|---|---|---|---|
| 0.6952 | 0.0625 | 48 | 0.7022 | 0.5244 |
| 0.5982 | 1.0625 | 96 | 0.6475 | 0.6463 |
| 0.4329 | 2.0625 | 144 | 0.5911 | 0.7134 |
| 0.3752 | 3.0625 | 192 | 0.5338 | 0.7378 |
| 0.2202 | 4.0625 | 240 | 0.5109 | 0.75 |
| 0.1893 | 5.0625 | 288 | 0.4991 | 0.7439 |
| 0.1454 | 6.0625 | 336 | 0.5313 | 0.7439 |
| 0.0931 | 7.0625 | 384 | 0.5668 | 0.7439 |
| 0.0657 | 8.0625 | 432 | 0.6028 | 0.7622 |
| 0.0704 | 9.0625 | 480 | 0.6340 | 0.7744 |
| 0.0298 | 10.0625 | 528 | 0.6770 | 0.7683 |
| 0.031 | 11.0625 | 576 | 0.7089 | 0.7805 |
| 0.0265 | 12.0625 | 624 | 0.7415 | 0.7683 |
| 0.0238 | 13.0625 | 672 | 0.7703 | 0.7744 |
| 0.0143 | 14.0625 | 720 | 0.7857 | 0.7744 |
| 0.0082 | 15.0625 | 768 | 0.7922 | 0.7683 |
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