metadata
tags:
- generated_from_trainer
model-index:
- name: GraphCodebert-gpt2
results: []
GraphCodebert-gpt2
This model is a fine-tuned version of 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