Training procedure

We finetuned Falcon-7B LLM on Python-Code-Instructions Dataset (iamtarun/python_code_instructions_18k_alpaca) for 10 epochs or ~ 23,000 steps using MonsterAPI no-code LLM finetuner.

The dataset contains problem descriptions and code in python language. This dataset is taken from sahil2801/code_instructions_120k, which adds a prompt column in alpaca style.

The finetuning session got completed in 7.3 hours and costed us only $17.5 for the entire finetuning run!

Hyperparameters & Run details:

  • Model Path: tiiuae/falcon-7b
  • Dataset: iamtarun/python_code_instructions_18k_alpaca
  • Learning rate: 0.0002
  • Number of epochs: 10
  • Data split: Training: 95% / Validation: 5%
  • Gradient accumulation steps: 1

Framework versions

  • PEFT 0.4.0

Loss metrics:

training loss

Downloads last month
3
Inference API
Unable to determine this model’s pipeline type. Check the docs .

Model tree for monsterapi/falcon-7b-python-code-instructions-18k-alpaca

Base model

tiiuae/falcon-7b
Adapter
(166)
this model

Dataset used to train monsterapi/falcon-7b-python-code-instructions-18k-alpaca