VideoMAE_BdSLW60_FrameRate_Corrected_with_Augment_20_epoch_RQ_GB
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: 0.5902
- Accuracy: 0.915
- Precision: 0.9412
- Recall: 0.915
- F1: 0.9057
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: 18560
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
---|---|---|---|---|---|---|---|
9.3789 | 0.0501 | 929 | 2.4070 | 0.4117 | 0.4786 | 0.4117 | 0.3632 |
2.3248 | 1.0501 | 1858 | 0.8424 | 0.7817 | 0.8018 | 0.7817 | 0.7540 |
0.858 | 2.0501 | 2787 | 0.6534 | 0.8233 | 0.8511 | 0.8233 | 0.8072 |
0.5065 | 3.0501 | 3716 | 0.5403 | 0.8733 | 0.9145 | 0.8733 | 0.8657 |
0.3166 | 4.0501 | 4645 | 1.0851 | 0.8317 | 0.8330 | 0.8317 | 0.8113 |
0.2901 | 5.0501 | 5574 | 0.9035 | 0.8367 | 0.8630 | 0.8367 | 0.8234 |
0.2002 | 6.0501 | 6503 | 0.8559 | 0.88 | 0.8737 | 0.88 | 0.8648 |
0.3852 | 7.0501 | 7432 | 0.6272 | 0.8883 | 0.9167 | 0.8883 | 0.8889 |
0.1676 | 8.0501 | 8361 | 0.7550 | 0.885 | 0.9165 | 0.885 | 0.8753 |
0.1147 | 9.0501 | 9290 | 0.7963 | 0.8717 | 0.8853 | 0.8717 | 0.8587 |
0.1002 | 10.0501 | 10219 | 0.7064 | 0.8917 | 0.9123 | 0.8917 | 0.8862 |
0.1555 | 11.0501 | 11148 | 0.6789 | 0.9017 | 0.9237 | 0.9017 | 0.8961 |
0.0757 | 12.0501 | 12077 | 0.9329 | 0.88 | 0.9259 | 0.88 | 0.8687 |
0.0246 | 13.0501 | 13006 | 0.6579 | 0.9033 | 0.9194 | 0.9033 | 0.8998 |
0.1073 | 14.0501 | 13935 | 0.3330 | 0.94 | 0.9503 | 0.94 | 0.9370 |
0.0087 | 15.0501 | 14864 | 1.1771 | 0.8533 | 0.8747 | 0.8533 | 0.8383 |
0.0005 | 16.0501 | 15793 | 0.6474 | 0.9017 | 0.9223 | 0.9017 | 0.8936 |
0.0018 | 17.0501 | 16722 | 0.6391 | 0.9067 | 0.9130 | 0.9067 | 0.8952 |
0.0001 | 18.0501 | 17651 | 0.6105 | 0.9167 | 0.9447 | 0.9167 | 0.9087 |
0.0 | 19.0490 | 18560 | 0.5902 | 0.915 | 0.9412 | 0.915 | 0.9057 |
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