videomae-base-finetuned-Risky-situations
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: 0.2880
- Accuracy: 0.8462
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-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 250
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.4854 | 0.1 | 25 | 0.0940 | 1.0 |
0.2925 | 1.1 | 50 | 0.0021 | 1.0 |
0.0187 | 2.1 | 75 | 0.3059 | 0.9167 |
0.0004 | 3.1 | 100 | 2.2330 | 0.6667 |
0.0005 | 4.1 | 125 | 0.0003 | 1.0 |
0.0003 | 5.1 | 150 | 0.0003 | 1.0 |
0.3102 | 6.1 | 175 | 1.2503 | 0.75 |
0.0003 | 7.1 | 200 | 0.0002 | 1.0 |
0.0002 | 8.1 | 225 | 0.0003 | 1.0 |
0.0002 | 9.1 | 250 | 0.0004 | 1.0 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Base model
MCG-NJU/videomae-base