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videomae-base-finetuned-kinetics-0414_final_5sec_org_ab7_val_inside_train_04_except259
d2o2ji/videomae-base-finetuned-kinetics-0414_final_5sec_org_ab7_val_inside_train_04_except259
videomae-base-finetuned-kinetics-0414_final_5sec_org_ab7_val_inside_train_04_except259 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 13, 2025
- Updated
- Apr 14, 2025
- SHA
- 3a31e4a6
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-0414_final_5sec_org_ab7_val_inside_train_04_except259
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: 0.3400
- Accuracy: 0.9191
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: 65100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0023 | 0.0100 | 652 | 0.2548 | 0.9225 |
| 0.3538 | 1.0100 | 1304 | 0.3333 | 0.8849 |
| 0.0063 | 2.0100 | 1956 | 0.3621 | 0.8825 |
| 0.0327 | 3.0100 | 2608 | 0.3076 | 0.9092 |
| 0.0265 | 4.0100 | 3260 | 0.5143 | 0.8684 |
| 0.0024 | 5.0100 | 3912 | 1.0078 | 0.7666 |
| 0.0045 | 6.0100 | 4564 | 1.0399 | 0.8074 |
| 0.0013 | 7.0100 | 5216 | 0.3645 | 0.8794 |
| 0.0055 | 8.0100 | 5868 | 0.7912 | 0.8246 |
| 0.6097 | 9.0100 | 6520 | 1.5637 | 0.7291 |
| 0.0004 | 10.0100 | 7172 | 0.5695 | 0.8724 |
| 0.0004 | 11.0100 | 7824 | 0.5662 | 0.8622 |
| 0.0021 | 12.0100 | 8476 | 1.0695 | 0.8105 |
| 0.0091 | 13.0100 | 9128 | 0.6833 | 0.8449 |
| 0.0004 | 14.0100 | 9780 | 0.5948 | 0.8614 |
| 0.0052 | 15.0100 | 10432 | 0.8243 | 0.8371 |
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 13, 2025
- Updated
- Apr 14, 2025