Llama-2-7b-hf-finetuned-py-to-cpp

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3938

Test evaluation:

  • BLEU: 60.09
  • COMET: 87.40
  • CODEBLEU: 74.17
    • N-gram match: 63.15
    • Weighted n-gram match: 78.82
    • Syntax match: 72.65
    • Dataflow match: 82.08

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

Training Loss Epoch Step Validation Loss
No log 0.99 67 0.6338
No log 2.0 135 0.4313
No log 2.98 201 0.3938

Framework versions

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