Code-Llama-3-8B-finetuned-py-to-cpp

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Code-Llama-3-8B-finetuned-py-to-cpp

This model is a fine-tuned version of ajibawa-2023/Code-Llama-3-8B on the XLCoST (Python-C++) dataset, restricted to code snippets of <= 128 tokens long. It achieves the following results on the evaluation set:

• Loss: 0.4550

Test set:

• BLEU: 38.48
• COMET: 79.28
• CodeBLEU: 64.11
  • N-gram match score: 40.15
  • Weighted n-gram match score: 77.11
  • Syntax match score: 67.02
  • Dataflow match score: 72.13

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 8
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 100
• num_epochs: 3

Training results

Framework versions

• Transformers 4.33.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.13.3