videomae-base-finetuned-2
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: 0.4272
- Accuracy: 0.9182
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: 4
- eval_batch_size: 4
- 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: 925
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9244 | 0.2011 | 186 | 0.9936 | 0.5818 |
| 0.3114 | 1.2011 | 372 | 1.0746 | 0.6818 |
| 0.3265 | 2.2011 | 558 | 0.7547 | 0.8364 |
| 0.1401 | 3.2011 | 744 | 0.5196 | 0.9 |
| 0.0014 | 4.1957 | 925 | 0.4272 | 0.9182 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.1.0+cpu
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for 2nzi/videomae-surf-analytics
Base model
MCG-NJU/videomae-base