---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CodeBERTa-commit-message-autocomplete
  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. -->

# CodeBERTa-commit-message-autocomplete

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: 1.7327
- Accuracy: 0.6612

## 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: 42
- eval_batch_size: 42
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 126
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 325  | 2.6847          | 0.5185   |
| 3.367         | 2.0   | 650  | 2.4055          | 0.5573   |
| 3.367         | 3.0   | 975  | 2.2742          | 0.5766   |
| 2.4354        | 4.0   | 1300 | 2.1065          | 0.6057   |
| 2.1925        | 5.0   | 1625 | 2.0764          | 0.6053   |
| 2.1925        | 6.0   | 1950 | 2.0169          | 0.6172   |
| 2.0217        | 7.0   | 2275 | 1.9270          | 0.6209   |
| 1.9424        | 8.0   | 2600 | 1.9326          | 0.6318   |
| 1.9424        | 9.0   | 2925 | 1.8849          | 0.6321   |
| 1.8485        | 10.0  | 3250 | 1.8834          | 0.6422   |
| 1.7847        | 11.0  | 3575 | 1.8213          | 0.6481   |
| 1.7847        | 12.0  | 3900 | 1.8674          | 0.6374   |
| 1.719         | 13.0  | 4225 | 1.7865          | 0.6473   |
| 1.6847        | 14.0  | 4550 | 1.8005          | 0.6523   |
| 1.6847        | 15.0  | 4875 | 1.8039          | 0.6516   |
| 1.6274        | 16.0  | 5200 | 1.7457          | 0.6617   |
| 1.5833        | 17.0  | 5525 | 1.7456          | 0.6526   |
| 1.5833        | 18.0  | 5850 | 1.7314          | 0.6626   |
| 1.5485        | 19.0  | 6175 | 1.7605          | 0.6590   |
| 1.5448        | 20.0  | 6500 | 1.7694          | 0.6592   |
| 1.5448        | 21.0  | 6825 | 1.7327          | 0.6612   |


### Framework versions

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