RALL_RGBCROP_Aug16F-polynomial
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: 0.5478
- Accuracy: 0.8635
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3462
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4872 | 0.0835 | 289 | 0.5884 | 0.6667 |
0.2293 | 1.0835 | 578 | 0.5230 | 0.7975 |
0.0214 | 2.0835 | 867 | 0.7384 | 0.8016 |
0.0423 | 3.0835 | 1156 | 0.8912 | 0.8139 |
0.0008 | 4.0835 | 1445 | 1.0195 | 0.8016 |
0.0004 | 5.0835 | 1734 | 1.0783 | 0.7996 |
0.0003 | 6.0835 | 2023 | 1.1355 | 0.8016 |
0.0002 | 7.0835 | 2312 | 1.1726 | 0.7935 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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Base model
MCG-NJU/videomae-base-finetuned-kinetics