metadata
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CommitPredictor
results: []
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: 0.5256
- Accuracy: 0.8924
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: 1.6938444694890367e-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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7816 | 1.0 | 2440 | 0.6604 | 0.8650 |
| 0.6888 | 2.0 | 4880 | 0.6062 | 0.8771 |
| 0.6499 | 3.0 | 7320 | 0.5908 | 0.8798 |
| 0.6186 | 4.0 | 9760 | 0.5603 | 0.8847 |
| 0.5839 | 5.0 | 12200 | 0.5449 | 0.8884 |
| 0.5767 | 6.0 | 14640 | 0.5387 | 0.8890 |
| 0.5776 | 7.0 | 17080 | 0.5394 | 0.8895 |
| 0.5549 | 8.0 | 19520 | 0.5292 | 0.8912 |
| 0.5582 | 9.0 | 21960 | 0.5294 | 0.8908 |
| 0.5566 | 10.0 | 24400 | 0.5256 | 0.8924 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2