Downloads · 30 days
21
50% of all-time downloads
videomae-base-finetuned-ucf101-subset
tenFnAN/videomae-base-finetuned-ucf101-subset
videomae-base-finetuned-ucf101-subset is a video classification model from tenFnAN. 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
42
Public
Parameters
86.2M
3.8 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
- Dec 9, 2024
- Updated
- Dec 9, 2024
- SHA
- 4f5f597b
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. -->
videomae-base-finetuned-ucf101-subset
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0826
- Accuracy: 0.9857
- F1: 0.9858
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-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: 148
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.4261 | 0.2568 | 38 | 0.4304 | 0.8286 | 0.7838 |
| 0.1438 | 1.2568 | 76 | 0.2029 | 0.9143 | 0.9114 |
| 0.0618 | 2.2568 | 114 | 0.1453 | 0.9429 | 0.9427 |
| 0.034 | 3.2297 | 148 | 0.0826 | 0.9857 | 0.9858 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1
- Datasets 2.19.1
- Tokenizers 0.20.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Dec 9, 2024
- Updated
- Dec 9, 2024