---
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: 1.7476
- Accuracy: 0.6825

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 2.655         | 1.0   | 599   | 2.1802          | 0.5963   |
| 2.2909        | 2.0   | 1198  | 2.0666          | 0.6172   |
| 2.1673        | 3.0   | 1797  | 2.0162          | 0.6197   |
| 2.0743        | 4.0   | 2396  | 1.9740          | 0.6283   |
| 1.9895        | 5.0   | 2995  | 1.9439          | 0.6338   |
| 1.8841        | 6.0   | 3594  | 1.9338          | 0.6291   |
| 1.8547        | 7.0   | 4193  | 1.7883          | 0.6559   |
| 1.7867        | 8.0   | 4792  | 1.8879          | 0.6436   |
| 1.7491        | 9.0   | 5391  | 1.8640          | 0.6445   |
| 1.7008        | 10.0  | 5990  | 1.7935          | 0.6591   |
| 1.631         | 11.0  | 6589  | 1.7864          | 0.6556   |
| 1.6094        | 12.0  | 7188  | 1.7964          | 0.6541   |
| 1.5755        | 13.0  | 7787  | 1.7675          | 0.6652   |
| 1.5787        | 14.0  | 8386  | 1.8498          | 0.6515   |
| 1.5235        | 15.0  | 8985  | 1.7363          | 0.6674   |
| 1.4996        | 16.0  | 9584  | 1.7428          | 0.6641   |
| 1.4571        | 17.0  | 10183 | 1.7004          | 0.6790   |
| 1.4617        | 18.0  | 10782 | 1.7714          | 0.6635   |
| 1.4219        | 19.0  | 11381 | 1.8232          | 0.6563   |
| 1.3959        | 20.0  | 11980 | 1.7245          | 0.6752   |
| 1.3801        | 21.0  | 12579 | 1.7234          | 0.6750   |
| 1.3549        | 22.0  | 13178 | 1.6884          | 0.6817   |
| 1.3227        | 23.0  | 13777 | 1.7566          | 0.6687   |
| 1.3455        | 24.0  | 14376 | 1.7102          | 0.6745   |
| 1.3239        | 25.0  | 14975 | 1.7388          | 0.6730   |
| 1.3066        | 26.0  | 15574 | 1.7391          | 0.6790   |
| 1.2598        | 27.0  | 16173 | 1.6754          | 0.6869   |
| 1.2552        | 28.0  | 16772 | 1.6499          | 0.6798   |
| 1.2431        | 29.0  | 17371 | 1.7397          | 0.6740   |
| 1.2115        | 30.0  | 17970 | 1.7096          | 0.6745   |
| 1.1842        | 31.0  | 18569 | 1.7159          | 0.6751   |
| 1.1799        | 32.0  | 19168 | 1.7341          | 0.6788   |
| 1.1755        | 33.0  | 19767 | 1.7557          | 0.6652   |
| 1.1704        | 34.0  | 20366 | 1.7147          | 0.6771   |
| 1.1427        | 35.0  | 20965 | 1.7631          | 0.6670   |
| 1.1464        | 36.0  | 21564 | 1.7083          | 0.6750   |
| 1.1179        | 37.0  | 22163 | 1.6978          | 0.6718   |
| 1.1247        | 38.0  | 22762 | 1.7205          | 0.6757   |
| 1.1204        | 39.0  | 23361 | 1.7403          | 0.6663   |
| 1.0939        | 40.0  | 23960 | 1.6621          | 0.6852   |
| 1.0904        | 41.0  | 24559 | 1.7671          | 0.6667   |
| 1.0815        | 42.0  | 25158 | 1.7304          | 0.6789   |
| 1.0879        | 43.0  | 25757 | 1.7346          | 0.6858   |
| 1.0718        | 44.0  | 26356 | 1.7841          | 0.6691   |
| 1.0599        | 45.0  | 26955 | 1.7482          | 0.6742   |
| 1.0815        | 46.0  | 27554 | 1.6738          | 0.6823   |
| 1.0812        | 47.0  | 28153 | 1.7573          | 0.6799   |
| 1.0529        | 48.0  | 28752 | 1.6627          | 0.6849   |
| 1.0675        | 49.0  | 29351 | 1.6641          | 0.6785   |
| 1.0593        | 50.0  | 29950 | 1.7476          | 0.6825   |


### Framework versions

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