---
tags:
- generated_from_trainer
model-index:
- name: GraphCodeBert-Moreepcohs
  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. -->

# GraphCodeBert-Moreepcohs

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3134
- Rouge2 Precision: 0.259
- Rouge2 Recall: 0.2528
- Rouge2 Fmeasure: 0.25
- Bleu Score: 0.2387

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | Bleu Score |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|:----------:|
| 5.8439        | 0.87  | 1500  | 4.1071          | 0.1478           | 0.1394        | 0.139           | 0.1384     |
| 3.7868        | 1.73  | 3000  | 3.6540          | 0.1742           | 0.1731        | 0.1697          | 0.1777     |
| 3.4877        | 2.6   | 4500  | 3.4311          | 0.205            | 0.1966        | 0.1959          | 0.193      |
| 3.0162        | 3.46  | 6000  | 3.3283          | 0.2249           | 0.2162        | 0.2142          | 0.2124     |
| 2.9085        | 4.33  | 7500  | 3.2684          | 0.2418           | 0.2312        | 0.2303          | 0.2233     |
| 2.5761        | 5.2   | 9000  | 3.2578          | 0.2427           | 0.2398        | 0.2354          | 0.2293     |
| 2.4163        | 6.06  | 10500 | 3.3048          | 0.2596           | 0.2516        | 0.2498          | 0.2386     |
| 2.2094        | 6.93  | 12000 | 3.2825          | 0.2561           | 0.2529        | 0.2492          | 0.2396     |
| 2.0907        | 7.79  | 13500 | 3.3134          | 0.259            | 0.2528        | 0.25            | 0.2387     |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2