---
license: other
license_name: yi-license
license_link: LICENSE
tags:
- lora
- qlora
- adapter
---
This is not an instruct fine tune, instead it's an attempt to de-contaminate the model, remove gptslop and refusals. I want model to feel like it was trained on human data, not synthetic one.


About 961 steps total, Yi-34B-200K llamafied DPO trained for 1 epoch on rawrr_v2 dataset via unsloth qlora at prompt length of 400 and max length of 700, lr 0.000045 \
Model initialized with max_positional_embeddings of 4096 to not OOM. \
Training done on RTX 3090 Ti in about 14 hours. \
Average mem usage was like 23.89 / 23.99 GiB, so very close to OOM at all times. \
I trained it with XFCE on one 1080p monitor loaded up, on more fancy DM it would probably OOM with the same setup. \
I am not sure what's the purpose of max_prompt_length being separate from max_length, so I may have used it wrong, I should read up on it. \
Script I used to do this fine-tune is in the repo. I used chatml prompt format. Now I plan to fine-tune this on AEZAKMI v3 dataset soon.