---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
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: 0.4811
- Accuracy: 0.8991
- F1: 0.8991
- Bleu4: 0.9479

## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Bleu4  |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
| 1.143         | 1.0   | 687   | 0.6993          | 0.8563   | 0.8563 | 0.8531 |
| 0.7772        | 2.0   | 1374  | 0.6482          | 0.8677   | 0.8677 | 0.9036 |
| 0.6738        | 3.0   | 2061  | 0.6211          | 0.8734   | 0.8734 | 0.8189 |
| 0.6544        | 4.0   | 2748  | 0.5942          | 0.8782   | 0.8782 | 0.9196 |
| 0.6295        | 5.0   | 3435  | 0.5805          | 0.8815   | 0.8815 | 0.8079 |
| 0.5966        | 6.0   | 4122  | 0.5609          | 0.8838   | 0.8838 | 0.8186 |
| 0.5916        | 7.0   | 4809  | 0.5514          | 0.8870   | 0.8870 | 0.9103 |
| 0.5732        | 8.0   | 5496  | 0.5492          | 0.8861   | 0.8861 | 0.8067 |
| 0.5559        | 9.0   | 6183  | 0.5389          | 0.8881   | 0.8881 | 0.9353 |
| 0.5511        | 10.0  | 6870  | 0.5257          | 0.8901   | 0.8901 | 0.9297 |
| 0.5345        | 11.0  | 7557  | 0.5319          | 0.8905   | 0.8905 | 0.9363 |
| 0.5287        | 12.0  | 8244  | 0.5220          | 0.8911   | 0.8911 | 0.8816 |
| 0.5226        | 13.0  | 8931  | 0.5139          | 0.8938   | 0.8938 | 0.9438 |
| 0.5147        | 14.0  | 9618  | 0.5124          | 0.8929   | 0.8929 | 0.9145 |
| 0.511         | 15.0  | 10305 | 0.5131          | 0.8932   | 0.8932 | 0.8570 |
| 0.4996        | 16.0  | 10992 | 0.4997          | 0.8964   | 0.8964 | 0.9287 |
| 0.4949        | 17.0  | 11679 | 0.5033          | 0.8958   | 0.8958 | 0.9460 |
| 0.4882        | 18.0  | 12366 | 0.5003          | 0.8971   | 0.8971 | 0.7739 |
| 0.4837        | 19.0  | 13053 | 0.4914          | 0.8979   | 0.8979 | 0.9014 |
| 0.4822        | 20.0  | 13740 | 0.4962          | 0.8963   | 0.8963 | 0.9330 |
| 0.4778        | 21.0  | 14427 | 0.4844          | 0.8971   | 0.8971 | 0.8454 |
| 0.4704        | 22.0  | 15114 | 0.4809          | 0.8988   | 0.8988 | 0.9274 |
| 0.4676        | 23.0  | 15801 | 0.4735          | 0.9009   | 0.9009 | 0.9445 |
| 0.4663        | 24.0  | 16488 | 0.4792          | 0.8990   | 0.8990 | 0.9001 |
| 0.4605        | 25.0  | 17175 | 0.4826          | 0.8995   | 0.8995 | 0.8313 |
| 0.4621        | 26.0  | 17862 | 0.4811          | 0.8991   | 0.8991 | 0.9479 |


### Framework versions

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