distilhubert-finetuned-mechanicalkeystrokes
This model is a fine-tuned version of ntu-spml/distilhubert on the MechanicalKeystrokes dataset. It achieves the following results on the evaluation set:
- Loss: 0.1155
- Accuracy: 0.9667
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.2923 | 1.0 | 30 | 2.3063 | 0.0333 |
| 2.2788 | 2.0 | 60 | 2.2863 | 0.1333 |
| 2.1377 | 3.0 | 90 | 2.1583 | 0.35 |
| 1.8769 | 4.0 | 120 | 1.8170 | 0.6167 |
| 1.5083 | 5.0 | 150 | 1.4282 | 0.7833 |
| 1.0911 | 6.0 | 180 | 1.0241 | 0.9333 |
| 0.7235 | 7.0 | 210 | 0.7131 | 0.9667 |
| 0.4517 | 8.0 | 240 | 0.4509 | 0.9667 |
| 0.2529 | 9.0 | 270 | 0.2682 | 0.9833 |
| 0.14 | 10.0 | 300 | 0.1799 | 0.9833 |
| 0.0791 | 11.0 | 330 | 0.1155 | 0.9667 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1
- Datasets 2.19.0
- Tokenizers 0.19.1
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