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hugo-albert/
Code-Llama-3-8B-finetuned-py-to-cpp

Name: Code-Llama-3-8B-finetuned-py-to-cpp
Availability: InStock

transformers

generated_from_trainer

text-generation

conversational

ajibawa-2023/Code-Llama-3-8B

finetune

llama3

endpoints_compatible

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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

Training Loss	Epoch	Step	Validation Loss
No log	0.99	87	0.5468
No log	2.0	175	0.4626
No log	2.98	261	0.4550

Framework versions

Transformers 4.33.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.13.3

hugo-albert/Code-Llama-3-8B-finetuned-py-to-cpp

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

hugo-albert/
Code-Llama-3-8B-finetuned-py-to-cpp