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videomae-base-finetuned-ucf101-subset
cdofitas/videomae-base-finetuned-ucf101-subset
videomae-base-finetuned-ucf101-subset is a video classification model from cdofitas. 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. --
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At a glance
- Task
- Video Classification
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- videomae
- Access
- Public
- Created
- Nov 9, 2023
- Updated
- Dec 19, 2023
- SHA
- cdb4a274
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: 1.1144
- Accuracy: 0.5987
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: 16
- eval_batch_size: 16
- 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: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.5857 | 0.04 | 22 | 1.5601 | 0.3459 |
| 1.5269 | 1.04 | 44 | 1.4939 | 0.3151 |
| 1.3172 | 2.04 | 66 | 1.1239 | 0.4658 |
| 1.2214 | 3.04 | 88 | 1.1980 | 0.4623 |
| 1.208 | 4.04 | 110 | 1.2465 | 0.4555 |
| 1.0422 | 5.04 | 132 | 1.2294 | 0.4966 |
| 1.0219 | 6.04 | 154 | 1.1516 | 0.5240 |
| 0.9113 | 7.04 | 176 | 1.2117 | 0.5068 |
| 1.035 | 8.04 | 198 | 1.0770 | 0.5616 |
| 0.8992 | 9.04 | 220 | 1.0658 | 0.5582 |
| 0.7292 | 10.04 | 242 | 1.2217 | 0.5445 |
| 0.8545 | 11.04 | 264 | 1.0260 | 0.5514 |
| 0.5855 | 12.04 | 286 | 1.0646 | 0.5993 |
| 0.7059 | 13.04 | 308 | 1.1769 | 0.5582 |
| 0.8109 | 14.04 | 330 | 1.1800 | 0.5137 |
| 0.6262 | 15.04 | 352 | 1.0740 | 0.5890 |
| 0.6297 | 16.04 | 374 | 1.0434 | 0.5719 |
| 0.7063 | 17.04 | 396 | 1.0205 | 0.5548 |
| 0.587 | 18.04 | 418 | 0.9799 | 0.6027 |
| 0.6087 | 19.04 | 440 | 0.9967 | 0.6164 |
| 0.5973 | 20.04 | 462 | 0.9683 | 0.6096 |
| 0.6971 | 21.04 | 484 | 1.0395 | 0.6027 |
| 0.6395 | 22.03 | 500 | 1.0663 | 0.5993 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.13.1
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Nov 9, 2023
- Updated
- Dec 19, 2023