---
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: 0.5096
- Accuracy: 0.8933

## 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: 21
- eval_batch_size: 21
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 63
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1808        | 1.0   | 599   | 0.7826          | 0.8420   |
| 0.8381        | 2.0   | 1198  | 0.7008          | 0.8581   |
| 0.7733        | 3.0   | 1797  | 0.6717          | 0.8639   |
| 0.7416        | 4.0   | 2396  | 0.6460          | 0.8682   |
| 0.7143        | 5.0   | 2995  | 0.6331          | 0.8708   |
| 0.683         | 6.0   | 3594  | 0.6243          | 0.8723   |
| 0.6609        | 7.0   | 4193  | 0.6151          | 0.8744   |
| 0.6547        | 8.0   | 4792  | 0.5987          | 0.8765   |
| 0.6467        | 9.0   | 5391  | 0.5969          | 0.8776   |
| 0.6366        | 10.0  | 5990  | 0.5890          | 0.8786   |
| 0.6176        | 11.0  | 6589  | 0.5785          | 0.8801   |
| 0.6106        | 12.0  | 7188  | 0.5813          | 0.8803   |
| 0.6026        | 13.0  | 7787  | 0.5644          | 0.8834   |
| 0.6005        | 14.0  | 8386  | 0.5600          | 0.8841   |
| 0.5965        | 15.0  | 8985  | 0.5653          | 0.8832   |
| 0.5851        | 16.0  | 9584  | 0.5544          | 0.8850   |
| 0.5781        | 17.0  | 10183 | 0.5543          | 0.8849   |
| 0.5732        | 18.0  | 10782 | 0.5464          | 0.8862   |
| 0.5713        | 19.0  | 11381 | 0.5448          | 0.8860   |
| 0.5678        | 20.0  | 11980 | 0.5452          | 0.8869   |
| 0.5615        | 21.0  | 12579 | 0.5395          | 0.8883   |
| 0.5543        | 22.0  | 13178 | 0.5383          | 0.8881   |
| 0.555         | 23.0  | 13777 | 0.5456          | 0.8870   |
| 0.5517        | 24.0  | 14376 | 0.5314          | 0.8890   |
| 0.5478        | 25.0  | 14975 | 0.5355          | 0.8878   |
| 0.5423        | 26.0  | 15574 | 0.5316          | 0.8892   |
| 0.5402        | 27.0  | 16173 | 0.5261          | 0.8903   |
| 0.5385        | 28.0  | 16772 | 0.5343          | 0.8884   |
| 0.5358        | 29.0  | 17371 | 0.5288          | 0.8894   |
| 0.5319        | 30.0  | 17970 | 0.5200          | 0.8912   |
| 0.5292        | 31.0  | 18569 | 0.5142          | 0.8923   |
| 0.529         | 32.0  | 19168 | 0.5174          | 0.8915   |
| 0.5233        | 33.0  | 19767 | 0.5253          | 0.8905   |
| 0.5236        | 34.0  | 20366 | 0.5135          | 0.8917   |
| 0.5269        | 35.0  | 20965 | 0.5127          | 0.8931   |
| 0.5145        | 36.0  | 21564 | 0.5182          | 0.8909   |
| 0.5192        | 37.0  | 22163 | 0.5185          | 0.8912   |
| 0.5154        | 38.0  | 22762 | 0.5160          | 0.8927   |
| 0.5131        | 39.0  | 23361 | 0.5135          | 0.8926   |
| 0.513         | 40.0  | 23960 | 0.5125          | 0.8924   |
| 0.5106        | 41.0  | 24559 | 0.5137          | 0.8919   |
| 0.5079        | 42.0  | 25158 | 0.5052          | 0.8935   |
| 0.508         | 43.0  | 25757 | 0.5172          | 0.8926   |
| 0.5104        | 44.0  | 26356 | 0.5062          | 0.8933   |
| 0.5066        | 45.0  | 26955 | 0.5076          | 0.8933   |
| 0.5085        | 46.0  | 27554 | 0.5123          | 0.8922   |
| 0.5064        | 47.0  | 28153 | 0.5102          | 0.8937   |
| 0.5058        | 48.0  | 28752 | 0.5127          | 0.8929   |
| 0.5028        | 49.0  | 29351 | 0.5164          | 0.8930   |
| 0.5036        | 50.0  | 29950 | 0.5096          | 0.8933   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2