As a base model used https://huggingface.co/eachadea/vicuna-13b-1.1
Finetuned on Teknium's GPTeacher dataset, unreleased Roleplay v2 dataset, GPT-4-LLM dataset Uncensored, WizardLM Uncensored and Nous Research Instruct Dataset
Approx 180k instructions, all from GPT-4, all cleaned of any OpenAI censorship/"As an AI Language Model" etc.
Base model still has OpenAI censorship. Soon, a new version will be released with cleaned vicuna from https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltere
Trained on 8 A100-80GB GPUs for 5 epochs following Alpaca deepspeed training code.
Nous Research Instruct Dataset will be released soon.
Prompt format is Alpaca:
### Instruction: ### Response:
or
### Instruction: ### Input: ### Response:
GPTeacher, Roleplay v2 by https://huggingface.co/teknium
Wizard LM by https://github.com/nlpxucan
Nous Research Instruct Dataset by https://huggingface.co/karan4d and https://huggingface.co/huemin
Benchmark results:
"arc_challenge": { "acc": 0.4189419795221843, "acc_stderr": 0.01441810695363901, "acc_norm": 0.439419795221843, "acc_norm_stderr": 0.014503747823580123 }, "arc_easy": { "acc": 0.7159090909090909, "acc_stderr": 0.009253921261885768, "acc_norm": 0.5867003367003367, "acc_norm_stderr": 0.010104361780747527 }, "boolq": { "acc": 0.8137614678899082, "acc_stderr": 0.006808882985424063 }, "hellaswag": { "acc": 0.5790679147580163, "acc_stderr": 0.004926996830194234, "acc_norm": 0.7518422624975104, "acc_norm_stderr": 0.004310610616845708 }, "openbookqa": { "acc": 0.288, "acc_stderr": 0.02027150383507522, "acc_norm": 0.436, "acc_norm_stderr": 0.0221989546414768 }, "piqa": { "acc": 0.7529923830250272, "acc_stderr": 0.010062268140772622, "acc_norm": 0.749727965179543, "acc_norm_stderr": 0.01010656188008979 }, "winogrande": { "acc": 0.6495659037095501, "acc_stderr": 0.01340904767667019 }
Compute provided by our project sponsor https://redmond.ai/