monsterapi/llama2_7b_norobots

Finetuning Overview:

Model Used: meta-llama/Llama-2-7b-hf

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 LLM finetuner, this finetuning:

• Was achieved with great cost-effectiveness.
• Completed in a total duration of 39mins 4secs for 1 epoch using an A6000 48GB GPU.
• Costed $1.313 for the entire epoch.

Hyperparameters & Additional Details:

• Epochs: 1
• Cost Per Epoch: $1.313
• Total Finetuning Cost: $1.313
• Model Path: meta-llama/Llama-2-7b-hf
• Learning Rate: 0.0002
• Data Split: 100% train
• Gradient Accumulation Steps: 4
• lora r: 32
• lora alpha: 64

Prompt Structure

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

Train loss :

license: apache-2.0