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videomae-base-finetuned-kinetics-0415_final_5sec_org_ab7_val_inside_train_04_except259
d2o2ji/videomae-base-finetuned-kinetics-0415_final_5sec_org_ab7_val_inside_train_04_except259
videomae-base-finetuned-kinetics-0415_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 14, 2025
- Updated
- Apr 15, 2025
- SHA
- d4e3e657
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-0415_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: 0.4084
- Accuracy: 0.8860
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 |
|---|---|---|---|---|
| 0.004 | 0.0100 | 652 | 0.3930 | 0.8818 |
| 0.471 | 1.0100 | 1304 | 0.3517 | 0.8982 |
| 0.003 | 2.0100 | 1956 | 0.6755 | 0.8207 |
| 0.2142 | 3.0100 | 2608 | 0.4885 | 0.8974 |
| 0.2487 | 4.0100 | 3260 | 0.6298 | 0.8575 |
| 0.0011 | 5.0100 | 3912 | 0.5771 | 0.8520 |
| 0.0004 | 6.0100 | 4564 | 0.6322 | 0.8583 |
| 0.0048 | 7.0100 | 5216 | 0.3840 | 0.8778 |
| 0.5816 | 8.0100 | 5868 | 0.7402 | 0.8426 |
| 0.0274 | 9.0100 | 6520 | 0.6222 | 0.8551 |
| 0.0002 | 10.0100 | 7172 | 0.6347 | 0.8872 |
| 0.0006 | 11.0100 | 7824 | 0.5242 | 0.8857 |
| 0.0001 | 12.0100 | 8476 | 1.1792 | 0.8058 |
| 0.0006 | 13.0100 | 9128 | 0.8387 | 0.8449 |
| 0.0003 | 14.0100 | 9780 | 0.4948 | 0.8872 |
| 0.0003 | 15.0100 | 10432 | 0.5446 | 0.8865 |
| 0.0008 | 16.0100 | 11084 | 0.7601 | 0.8583 |
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 14, 2025
- Updated
- Apr 15, 2025