CodeBertForClone-Detection
This model is a fine-tuned version of microsoft/codebert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4183
- Accuracy: 0.834
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 24000.0
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3291 | 1.0 | 5000 | 0.3769 | 0.8285 |
| 0.3053 | 2.0 | 10000 | 0.3781 | 0.8345 |
| 0.3319 | 3.0 | 15000 | 0.3811 | 0.847 |
| 0.3007 | 4.0 | 20000 | 0.3990 | 0.8413 |
| 0.291 | 5.0 | 25000 | 0.4183 | 0.834 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for ljcnju/CodeBertForClone-Detection
Base model
microsoft/codebert-base