monsterapi/mistral_7b_norobots

Finetuning Overview:

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

Dataset: HuggingFaceH4/no_robots

Dataset Insights:

No Robots is a high-quality dataset of 10,000 instructions and demonstrations created by skilled human annotators. This data can be used for supervised fine-tuning (SFT) to make language models follow instructions better.

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 1h 15m 3s for 2 epochs using an A6000 48GB GPU.
• Costed $2.525 for the entire 2 epochs.

Hyperparameters & Additional Details:

• Epochs: 2
• Cost Per Epoch: $1.26
• Total Finetuning Cost: $2.525
• Model Path: mistralai/Mistral-7B-v0.1
• Learning Rate: 0.0002
• Data Split: 100% train
• Gradient Accumulation Steps: 64
• lora r: 64
• lora alpha: 16

Prompt Structure

<|system|> </s> <|user|> [USER PROMPT] </s> <|assistant|> [ASSISTANT ANSWER] </s>

Train loss :

Benchmarking results :

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license: apache-2.0