CommitPredictor
This model is a fine-tuned version of microsoft/codebert-base-mlm on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8427
- Accuracy: 0.6409
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 292 | 2.2754 | 0.5767 |
2.5787 | 2.0 | 584 | 2.2006 | 0.5877 |
2.5787 | 3.0 | 876 | 2.0851 | 0.5953 |
2.2167 | 4.0 | 1168 | 2.0148 | 0.6142 |
2.2167 | 5.0 | 1460 | 1.9583 | 0.6144 |
2.064 | 6.0 | 1752 | 1.8846 | 0.6309 |
1.9626 | 7.0 | 2044 | 1.9399 | 0.6247 |
1.9626 | 8.0 | 2336 | 1.8423 | 0.6401 |
1.8671 | 9.0 | 2628 | 1.8065 | 0.6407 |
1.8671 | 10.0 | 2920 | 1.7582 | 0.6507 |
1.7957 | 11.0 | 3212 | 1.7978 | 0.6479 |
1.7226 | 12.0 | 3504 | 1.8058 | 0.6521 |
1.7226 | 13.0 | 3796 | 1.8427 | 0.6409 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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