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videomae-base-finetuned-kinetics-0403_final_only5sec
d2o2ji/videomae-base-finetuned-kinetics-0403_final_only5sec
videomae-base-finetuned-kinetics-0403_final_only5sec is a video classification model from d2o2ji. 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
- Apr 3, 2025
- Updated
- Apr 3, 2025
- SHA
- 33034828
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-kinetics-0403_final_only5sec
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: 0.9866
- Accuracy: 0.7954
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 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: 0.05
- training_steps: 62100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0258 | 0.0100 | 622 | 0.3408 | 0.8950 |
| 0.0148 | 1.0100 | 1244 | 0.3555 | 0.8603 |
| 0.0013 | 2.0100 | 1866 | 0.5279 | 0.8754 |
| 0.0044 | 3.0100 | 2488 | 0.8037 | 0.8283 |
| 0.0127 | 4.0100 | 3110 | 0.6375 | 0.8461 |
| 1.0048 | 5.0100 | 3732 | 1.2457 | 0.7811 |
| 0.0006 | 6.0100 | 4354 | 0.7576 | 0.8292 |
| 0.0003 | 7.0100 | 4976 | 0.4766 | 0.8968 |
| 0.0027 | 8.0100 | 5598 | 0.6147 | 0.8496 |
| 0.0012 | 9.0100 | 6220 | 0.6214 | 0.8345 |
| 0.0157 | 10.0100 | 6842 | 0.6998 | 0.8514 |
| 0.0099 | 11.0100 | 7464 | 1.1907 | 0.7847 |
| 0.0537 | 12.0100 | 8086 | 1.2955 | 0.8043 |
| 0.0001 | 13.0100 | 8708 | 1.1235 | 0.7972 |
| 0.0007 | 14.0100 | 9330 | 1.3138 | 0.7900 |
| 0.0028 | 15.0100 | 9952 | 1.0310 | 0.8221 |
| 0.0008 | 16.0100 | 10574 | 0.8199 | 0.8514 |
| 0.015 | 17.0100 | 11196 | 0.5774 | 0.8852 |
| 0.0002 | 18.0100 | 11818 | 0.9953 | 0.8407 |
| 0.6463 | 19.0100 | 12440 | 1.2704 | 0.8132 |
| 0.0001 | 20.0100 | 13062 | 1.0214 | 0.8203 |
| 0.0012 | 21.0100 | 13684 | 1.2372 | 0.8194 |
| 0.0001 | 22.0100 | 14306 | 1.0967 | 0.8372 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Video Classification
- Library
- transformers
- Type
- videomae
- License
- cc-by-nc-4.0
- Created
- Apr 3, 2025
- Updated
- Apr 3, 2025