---
tags:
- generated_from_trainer
model-index:
- name: GraphCodebert-gpt2
  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-gpt2

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: 3.6964
- Rouge2 Precision: 0.1809
- Rouge2 Recall: 0.1775
- Rouge2 Fmeasure: 0.1747

## 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: 2000
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| No log        | 0.29  | 500  | 5.0350          | 0.0889           | 0.0797        | 0.0819          |
| 6.0048        | 0.58  | 1000 | 4.4849          | 0.1159           | 0.116         | 0.1138          |
| 6.0048        | 0.87  | 1500 | 4.1607          | 0.151            | 0.1474        | 0.1452          |
| 4.2848        | 1.15  | 2000 | 4.0174          | 0.1558           | 0.1465        | 0.1471          |
| 4.2848        | 1.44  | 2500 | 3.8264          | 0.1786           | 0.1683        | 0.1685          |
| 3.8448        | 1.73  | 3000 | 3.6964          | 0.1809           | 0.1775        | 0.1747          |


### Framework versions

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