| | --- |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: CommitPredictor |
| | results: [] |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # CommitPredictor |
| |
|
| | This model is a fine-tuned version of [microsoft/codebert-base-mlm](https://huggingface.co/microsoft/codebert-base-mlm) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.5037 |
| | - Accuracy: 0.8963 |
| |
|
| | ## 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: 2.722963804424848e-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 | |
| | |:-------------:|:-----:|:-----:|:---------------:|:--------:| |
| | | 0.7479 | 1.0 | 2440 | 0.6350 | 0.8715 | |
| | | 0.6629 | 2.0 | 4880 | 0.5891 | 0.8793 | |
| | | 0.6252 | 3.0 | 7320 | 0.5720 | 0.8829 | |
| | | 0.5904 | 4.0 | 9760 | 0.5426 | 0.8883 | |
| | | 0.5549 | 5.0 | 12200 | 0.5284 | 0.8918 | |
| | | 0.5456 | 6.0 | 14640 | 0.5212 | 0.8927 | |
| | | 0.5452 | 7.0 | 17080 | 0.5206 | 0.8933 | |
| | | 0.5196 | 8.0 | 19520 | 0.5094 | 0.8948 | |
| | | 0.5193 | 9.0 | 21960 | 0.5078 | 0.8950 | |
| | | 0.5193 | 10.0 | 24400 | 0.5037 | 0.8963 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.25.1 |
| | - Pytorch 1.13.0+cu117 |
| | - Datasets 2.7.1 |
| | - Tokenizers 0.13.2 |
| |
|
