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--- |
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license: llama3 |
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base_model: ajibawa-2023/Code-Llama-3-8B |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: Code-Llama-3-8B-finetuned-py-to-cpp |
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results: [] |
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pipeline_tag: text-generation |
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library_name: transformers |
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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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# Code-Llama-3-8B-finetuned-py-to-cpp |
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This model is a fine-tuned version of [ajibawa-2023/Code-Llama-3-8B](https://huggingface.co/ajibawa-2023/Code-Llama-3-8B) on the [XLCoST](https://github.com/reddy-lab-code-research/XLCoST) (Python-C++) dataset, restricted to code snippets of <= 128 tokens long. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4550 |
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Test set: |
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- BLEU: 38.48 |
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- COMET: 79.28 |
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- CodeBLEU: 64.11 |
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- N-gram match score: 40.15 |
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- Weighted n-gram match score: 77.11 |
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- Syntax match score: 67.02 |
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- Dataflow match score: 72.13 |
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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: 0.0001 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 16 |
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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: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| No log | 0.99 | 87 | 0.5468 | |
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| No log | 2.0 | 175 | 0.4626 | |
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| No log | 2.98 | 261 | 0.4550 | |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.13.3 |
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``` |
