---
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