---
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: 1.9935
- Accuracy: 0.6325

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 448   | 2.4744          | 0.5376   |
| 2.9007        | 2.0   | 896   | 2.4149          | 0.5473   |
| 2.5284        | 3.0   | 1344  | 2.3077          | 0.5639   |
| 2.3292        | 4.0   | 1792  | 2.2617          | 0.5640   |
| 2.2692        | 5.0   | 2240  | 2.2155          | 0.5719   |
| 2.1766        | 6.0   | 2688  | 2.1555          | 0.5792   |
| 2.0842        | 7.0   | 3136  | 2.0758          | 0.6030   |
| 2.0268        | 8.0   | 3584  | 2.1446          | 0.5942   |
| 1.9416        | 9.0   | 4032  | 2.1110          | 0.5840   |
| 1.9416        | 10.0  | 4480  | 2.1379          | 0.5888   |
| 1.8969        | 11.0  | 4928  | 2.0461          | 0.6082   |
| 1.8247        | 12.0  | 5376  | 2.0585          | 0.6007   |
| 1.8038        | 13.0  | 5824  | 2.0541          | 0.6022   |
| 1.7601        | 14.0  | 6272  | 2.0832          | 0.6043   |
| 1.7086        | 15.0  | 6720  | 2.0224          | 0.6096   |
| 1.7087        | 16.0  | 7168  | 2.0853          | 0.6057   |
| 1.653         | 17.0  | 7616  | 2.0259          | 0.6124   |
| 1.5953        | 18.0  | 8064  | 1.9913          | 0.6207   |
| 1.6074        | 19.0  | 8512  | 1.9798          | 0.6157   |
| 1.6074        | 20.0  | 8960  | 2.0234          | 0.6033   |
| 1.5749        | 21.0  | 9408  | 1.9686          | 0.6197   |
| 1.535         | 22.0  | 9856  | 2.0068          | 0.6163   |
| 1.4942        | 23.0  | 10304 | 1.9486          | 0.6310   |
| 1.4765        | 24.0  | 10752 | 1.9502          | 0.6304   |
| 1.4558        | 25.0  | 11200 | 1.9509          | 0.6328   |
| 1.4617        | 26.0  | 11648 | 1.9903          | 0.6196   |
| 1.4224        | 27.0  | 12096 | 1.9849          | 0.6321   |
| 1.4019        | 28.0  | 12544 | 1.9781          | 0.6193   |
| 1.4019        | 29.0  | 12992 | 2.0661          | 0.6145   |
| 1.3624        | 30.0  | 13440 | 1.9948          | 0.6191   |
| 1.3517        | 31.0  | 13888 | 1.9117          | 0.6392   |
| 1.3613        | 32.0  | 14336 | 2.0300          | 0.6176   |
| 1.3428        | 33.0  | 14784 | 2.0005          | 0.6226   |
| 1.3257        | 34.0  | 15232 | 2.0079          | 0.6149   |
| 1.3127        | 35.0  | 15680 | 2.0231          | 0.6213   |
| 1.289         | 36.0  | 16128 | 1.9961          | 0.6296   |
| 1.2689        | 37.0  | 16576 | 1.9930          | 0.6221   |
| 1.2651        | 38.0  | 17024 | 1.9675          | 0.6314   |
| 1.2651        | 39.0  | 17472 | 1.9835          | 0.6220   |
| 1.2638        | 40.0  | 17920 | nan             | 0.6275   |
| 1.235         | 41.0  | 18368 | 2.0100          | 0.6299   |
| 1.2239        | 42.0  | 18816 | 2.0384          | 0.6152   |
| 1.2147        | 43.0  | 19264 | 2.0421          | 0.6209   |
| 1.1961        | 44.0  | 19712 | 2.0041          | 0.6212   |
| 1.1988        | 45.0  | 20160 | 1.9905          | 0.6230   |
| 1.2007        | 46.0  | 20608 | 2.0222          | 0.6275   |
| 1.2029        | 47.0  | 21056 | 1.9856          | 0.6361   |
| 1.1779        | 48.0  | 21504 | 2.0348          | 0.6184   |
| 1.1779        | 49.0  | 21952 | 1.9196          | 0.6324   |
| 1.1973        | 50.0  | 22400 | 1.9935          | 0.6325   |


### Framework versions

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