Last update for those following: https://www.reddit.com/r/LocalLLaMA/comments/1wvyc3e/update_3_post_training_yandexaliceai80ba3b/ Project in a sentence: An instruct finetune of ALiceAI-80B-A3B-Base capable of agentic work and conversation. I'm creating a shallow distill of qwen 3.8 27b on medium to teach the model chain of thought reasoning and conversation. All training is done locally on 3, 32gb v100s. Additionally, all the training data is being generated locally on said V100s via sftmill. Up to this point I've been doing training runs and live-streaming the progress. Well, I successfully completed my round 1 SFT and got to test. Good news: the model appears to be picking up chain of thought reasoning correctly and can respond conversationally. Bad news: not enough instruct SFT / badly underfit. While checkpoint #1 was technically functional, it's basically useless. My initial 5 million tokens (as I've deducted) didn't have enough breadth to properly teach the model general conversation ability - ambiguous questions or prompts further away from exact matches in the training data create a garbled output because it doesn't have enough ambiguous data to learn from. Next steps? I've opted not to release checkpoint #1 (we're going to call this 1.0 alpha or something) because it's basically useless, but I'll still be releasing my first working edition. I've increased the pace of my local synthetic data generator from 80tps to around 240tps total by adding the option to draw from multiple base URLs, so I have more distillation data coming [I'm currently generating on 3 seperate instances, with 4 parallel workers each. I'm creating an additional dataset of about 5M tokens again, but this time spread in a much broader general instruct direction, rather that the coding oriented version I had originally. I'm going to train on top of checkpoint 1.0 alpha at a reduced learning rate and hopefully come away with a more competent version. I'll be posting updates on the training again - I can do another live stream if you guys want, but I figured that since I don't have much to show yet, this would be my last update until I have a working initial checkpoint. I'm happy to share whatever if there's community interest though. I've mentioned in here before, but the resource for people interested: I created a off-policy distillation engine when I began this project that makes it very easy to create training data from a behavioral goal - e.g. I want a general instruct model -> raw training data. I created an OSS fork which is public at https://github.com/jackjusko/sftmill Thanks for following!   submitted by   /u/jjusko20 [link]   [comments]