Downloads · 30 days
8
2% of all-time downloads
videomae-base-finetuned-slrbd001
XenXeon/videomae-base-finetuned-slrbd001
videomae-base-finetuned-slrbd001 is a video classification model from XenXeon. 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
413
Public
Parameters
86.2M
345 MB 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
- Nov 27, 2023
- Updated
- Nov 27, 2023
- SHA
- 494d3350
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-slrbd001
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: 1.6389
- Accuracy: 0.25
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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 60
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.05 | 3 | 1.4887 | 0.25 |
| No log | 1.05 | 6 | 1.3967 | 0.0 |
| No log | 2.05 | 9 | 1.3822 | 0.375 |
| 1.4098 | 3.05 | 12 | 1.3607 | 0.375 |
| 1.4098 | 4.05 | 15 | 1.2716 | 0.5 |
| 1.4098 | 5.05 | 18 | 1.2074 | 0.5 |
| 1.2325 | 6.05 | 21 | 1.3363 | 0.25 |
| 1.2325 | 7.05 | 24 | 1.3342 | 0.25 |
| 1.2325 | 8.05 | 27 | 1.1540 | 0.375 |
| 0.8868 | 9.05 | 30 | 1.0971 | 0.5 |
| 0.8868 | 10.05 | 33 | 1.1247 | 0.375 |
| 0.8868 | 11.05 | 36 | 1.2616 | 0.25 |
| 0.8868 | 12.05 | 39 | 0.9747 | 0.375 |
| 0.8266 | 13.05 | 42 | 0.8311 | 0.375 |
| 0.8266 | 14.05 | 45 | 0.9191 | 0.375 |
| 0.8266 | 15.05 | 48 | 1.1805 | 0.25 |
| 0.8023 | 16.05 | 51 | 1.3324 | 0.25 |
| 0.8023 | 17.05 | 54 | 1.5051 | 0.25 |
| 0.8023 | 18.05 | 57 | 1.6055 | 0.25 |
| 0.7772 | 19.05 | 60 | 1.6389 | 0.25 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Nov 27, 2023
- Updated
- Nov 27, 2023