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README.md
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---
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tags:
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- generated_from_trainer
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model-index:
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- name: GraphCodebert-gpt2
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# GraphCodebert-gpt2
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.6964
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- Rouge2 Precision: 0.1809
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- Rouge2 Recall: 0.1775
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- Rouge2 Fmeasure: 0.1747
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 2000
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- num_epochs: 2
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| No log | 0.29 | 500 | 5.0350 | 0.0889 | 0.0797 | 0.0819 |
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| 6.0048 | 0.58 | 1000 | 4.4849 | 0.1159 | 0.116 | 0.1138 |
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| 6.0048 | 0.87 | 1500 | 4.1607 | 0.151 | 0.1474 | 0.1452 |
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| 4.2848 | 1.15 | 2000 | 4.0174 | 0.1558 | 0.1465 | 0.1471 |
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| 4.2848 | 1.44 | 2500 | 3.8264 | 0.1786 | 0.1683 | 0.1685 |
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| 3.8448 | 1.73 | 3000 | 3.6964 | 0.1809 | 0.1775 | 0.1747 |
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### Framework versions
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- Transformers 4.25.1
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- Pytorch 1.13.1+cu116
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- Datasets 2.8.0
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- Tokenizers 0.13.2
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