VideoMAE_BdSLW60_FrameRate_NOT_Corrected_with_Augment_20_epoch_RQ
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: 0.0470
- Accuracy: 0.9906
- Precision: 0.9913
- Recall: 0.9906
- F1: 0.9906
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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: 0.1
- training_steps: 17940
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
11.7722 | 0.05 | 897 | 2.3329 | 0.4482 | 0.4616 | 0.4482 | 0.3915 |
2.7045 | 1.0500 | 1795 | 0.6715 | 0.8471 | 0.8870 | 0.8471 | 0.8384 |
0.7855 | 2.0500 | 2693 | 0.2378 | 0.9412 | 0.9474 | 0.9412 | 0.9401 |
0.5503 | 3.0500 | 3591 | 0.1367 | 0.9635 | 0.9686 | 0.9635 | 0.9635 |
0.2537 | 4.05 | 4488 | 0.1621 | 0.9612 | 0.9658 | 0.9612 | 0.9608 |
0.2549 | 5.0500 | 5386 | 0.1229 | 0.9765 | 0.9789 | 0.9765 | 0.9761 |
0.3236 | 6.0500 | 6284 | 0.0916 | 0.9765 | 0.9799 | 0.9765 | 0.9763 |
0.2078 | 7.0500 | 7182 | 0.1703 | 0.96 | 0.9647 | 0.96 | 0.9600 |
0.1967 | 8.05 | 8079 | 0.1708 | 0.9706 | 0.9731 | 0.9706 | 0.9707 |
0.2457 | 9.0500 | 8977 | 0.1500 | 0.9718 | 0.9772 | 0.9718 | 0.9716 |
0.0204 | 10.0500 | 9875 | 0.1181 | 0.9812 | 0.9833 | 0.9812 | 0.9811 |
0.0753 | 11.0500 | 10773 | 0.1418 | 0.9753 | 0.9775 | 0.9753 | 0.9755 |
0.0568 | 12.05 | 11670 | 0.1563 | 0.9765 | 0.9791 | 0.9765 | 0.9763 |
0.0851 | 13.0500 | 12568 | 0.0903 | 0.9847 | 0.9856 | 0.9847 | 0.9846 |
0.0106 | 14.0500 | 13466 | 0.0935 | 0.9871 | 0.9881 | 0.9871 | 0.9869 |
0.0171 | 15.0500 | 14364 | 0.0429 | 0.9929 | 0.9934 | 0.9929 | 0.9929 |
0.0025 | 16.05 | 15261 | 0.0584 | 0.9882 | 0.9890 | 0.9882 | 0.9882 |
0.0006 | 17.0500 | 16159 | 0.0693 | 0.9882 | 0.9894 | 0.9882 | 0.9883 |
0.0001 | 18.0500 | 17057 | 0.0513 | 0.9906 | 0.9913 | 0.9906 | 0.9906 |
0.0001 | 19.0492 | 17940 | 0.0470 | 0.9906 | 0.9913 | 0.9906 | 0.9906 |
Framework versions
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.1
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Base model
MCG-NJU/videomae-base