| --- |
| 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: 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 |
| |
