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falcon
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Finetuning Overview:

Model Used: tiiuae/falcon-7b

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 1h 21m 21s for 3 epochs using an A6000 48GB GPU.
  • Costed $0.909 for 1 epoch.

Hyperparameters & Additional Details:

  • Epochs: 3
  • Cost Per Epoch: $0.909
  • Total Finetuning Cost: $2.727
  • Model Path: tiiuae/falcon-7b
  • 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 :

image/png

license: apache-2.0

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