monsterapi/mistral_7b_HalfEpoch_DolphinCoder

Finetuning Overview:

Model Used: mistralai/Mistral-7B-v0.1

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 7hrs 36min for 0.5 epochs using an A6000 48GB GPU.
• Costed $15.2 for the entire run

Hyperparameters & Additional Details:

• Epochs: 0.5
• Cost for full run: $15.2
• Model Path: mistralai/Mistral-7B-v0.1
• 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