RALL_RGBCROP_Aug16F-8B16F-lr5e6_2
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: 0.6144
- Accuracy: 0.8554
1.Best Learning Rate lr : 5e-6
Model description
More information needed
Intended uses & limitations
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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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3462
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4481 | 0.0835 | 289 | 0.5643 | 0.7485 |
0.203 | 1.0835 | 578 | 0.5270 | 0.8016 |
0.0444 | 2.0835 | 867 | 0.6951 | 0.8139 |
0.0038 | 3.0835 | 1156 | 0.8074 | 0.8282 |
0.0041 | 4.0835 | 1445 | 0.8784 | 0.8344 |
0.0005 | 5.0835 | 1734 | 0.9289 | 0.8344 |
0.0004 | 6.0835 | 2023 | 0.9893 | 0.8241 |
0.0003 | 7.0835 | 2312 | 1.0132 | 0.8323 |
0.0003 | 8.0835 | 2601 | 1.0356 | 0.8282 |
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