Zangs3011/mistral_7b_2EPOCH_DolphinCoder

Finetuning Overview:

Model Used: codellama/CodeLlama-7b-hf

Dataset: cognitivecomputations/dolphin-coder

Dataset Insights:

Dolphin-Coder dataset – a high-quality collection of 100,000+ coding questions and responses. It's perfect for supervised fine-tuning (SFT), and teaching language models to improve on coding-based tasks.

Finetuning Details:

With the utilization of MonsterAPI's no-code LLM finetuner, this finetuning:

• Was achieved with great cost-effectiveness.
• Completed in a total duration of 15hr 31mins for 1 epochs using an A6000 48GB GPU.
• Costed $31.31 for the entire 1 epoch.

Hyperparameters & Additional Details:

• Epochs: 1
• Total Finetuning Cost: $31.31
• Model Path: codellama/CodeLlama-7b-hf
• Learning Rate: 0.0002
• Data Split: 100% train
• Gradient Accumulation Steps: 128
• lora r: 32
• lora alpha: 64

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license: apache-2.0