CodeLlama_7B_nlp_pp

CodeLlama_7B_nlp_pp

This model is a fine-tuned version of codellama/CodeLlama-7b-hf on the AshtonIsNotHere/nlp_pp_code_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.4129
• Accuracy: 0.8968

Model description

This model has been fine-tuned for code completion on a dataset of NLP++ code.

Intended uses & limitations

More information needed

Training and evaluation data

Dataset consists of a combination of scraped NLP++ code and NLP++ code examples from the VisualText website.

Training procedure

This model is trained in a multinode, multi-gpu setup with DeepSpeed Z3. For more information on the training setup, check out the GitHub repo.

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.00012
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• total_eval_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 7.0

Training results

Framework versions

• Transformers 4.30.2
• Pytorch 2.0.1+cu117
• Datasets 2.13.0
• Tokenizers 0.13.3