---
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: 1.6621
- Accuracy: 0.6851

## 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
- num_epochs: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 299   | 2.2298          | 0.5874   |
| 2.5371        | 2.0   | 598   | 2.1358          | 0.6110   |
| 2.5371        | 3.0   | 897   | 2.0865          | 0.6056   |
| 2.1935        | 4.0   | 1196  | 2.0596          | 0.6179   |
| 2.1935        | 5.0   | 1495  | 1.9902          | 0.6305   |
| 2.0549        | 6.0   | 1794  | 1.9647          | 0.6274   |
| 1.9558        | 7.0   | 2093  | 1.9462          | 0.6290   |
| 1.9558        | 8.0   | 2392  | 1.9443          | 0.6261   |
| 1.8732        | 9.0   | 2691  | 1.9241          | 0.6317   |
| 1.8732        | 10.0  | 2990  | 1.8810          | 0.6461   |
| 1.798         | 11.0  | 3289  | 1.8232          | 0.6434   |
| 1.7427        | 12.0  | 3588  | 1.8621          | 0.6452   |
| 1.7427        | 13.0  | 3887  | 1.7853          | 0.6596   |
| 1.7124        | 14.0  | 4186  | 1.8741          | 0.6451   |
| 1.7124        | 15.0  | 4485  | 1.7989          | 0.6536   |
| 1.6683        | 16.0  | 4784  | 1.7783          | 0.6582   |
| 1.59          | 17.0  | 5083  | 1.7738          | 0.6642   |
| 1.59          | 18.0  | 5382  | 1.8241          | 0.6534   |
| 1.5773        | 19.0  | 5681  | 1.8739          | 0.6547   |
| 1.5773        | 20.0  | 5980  | 1.7439          | 0.6695   |
| 1.532         | 21.0  | 6279  | 1.7081          | 0.6705   |
| 1.4875        | 22.0  | 6578  | 1.7486          | 0.6662   |
| 1.4875        | 23.0  | 6877  | 1.7568          | 0.6656   |
| 1.466         | 24.0  | 7176  | 1.8062          | 0.6658   |
| 1.466         | 25.0  | 7475  | 1.7666          | 0.6704   |
| 1.448         | 26.0  | 7774  | 1.7219          | 0.6670   |
| 1.4121        | 27.0  | 8073  | 1.6704          | 0.6745   |
| 1.4121        | 28.0  | 8372  | 1.6966          | 0.6719   |
| 1.3984        | 29.0  | 8671  | 1.6789          | 0.6825   |
| 1.3984        | 30.0  | 8970  | 1.7001          | 0.6797   |
| 1.3586        | 31.0  | 9269  | 1.7262          | 0.6712   |
| 1.3433        | 32.0  | 9568  | 1.7446          | 0.6744   |
| 1.3433        | 33.0  | 9867  | 1.6961          | 0.6752   |
| 1.3366        | 34.0  | 10166 | 1.7180          | 0.6729   |
| 1.3366        | 35.0  | 10465 | 1.6608          | 0.6773   |
| 1.3227        | 36.0  | 10764 | 1.6820          | 0.6814   |
| 1.3025        | 37.0  | 11063 | 1.7324          | 0.6727   |
| 1.3025        | 38.0  | 11362 | 1.6705          | 0.6882   |
| 1.2933        | 39.0  | 11661 | 1.6891          | 0.6742   |
| 1.2933        | 40.0  | 11960 | 1.6533          | 0.6797   |
| 1.2826        | 41.0  | 12259 | 1.6851          | 0.6770   |
| 1.2784        | 42.0  | 12558 | 1.7140          | 0.6806   |
| 1.2784        | 43.0  | 12857 | 1.6869          | 0.6769   |
| 1.2703        | 44.0  | 13156 | 1.7068          | 0.6730   |
| 1.2703        | 45.0  | 13455 | 1.7376          | 0.6681   |
| 1.2492        | 46.0  | 13754 | 1.6944          | 0.6751   |
| 1.2619        | 47.0  | 14053 | 1.8112          | 0.6644   |
| 1.2619        | 48.0  | 14352 | 1.7553          | 0.6721   |
| 1.2465        | 49.0  | 14651 | 1.7040          | 0.6713   |
| 1.2465        | 50.0  | 14950 | 1.6621          | 0.6851   |


### Framework versions

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