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As a PM I can do some envelope math for you. Gpt3 was trained on 45terabytes of text and has 175billion parameters. So should be like 15mins to clone it and retrain. Two instead of three sounds like not much, but if you instead phrase it: “It reduces the Anxiety is high today reduce the stigma remember bear retro shirt it is in the first place but time by 168 hours”, that’s quite a performance boost >.< I know this is a joke, but the sheer scale of how wrong this is is hilarious. I’m training a 10 million parameter language model right now; 72 hours on a 3070 so far and it’s just finally starting to predict tokens other than “of” and “the”. I fully expect another 144 hours before it’s even usable for my downstream classification tasks. Be sure to not so subtly hint that "story points" are just a code word for "days". Well they're not. Everyone knows that they're supposed to represent complexity and not an actual unit of time. But let's just say, hypothetically, that they do.

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Is that after tuning learning rate? I don’t think I’d have bothered waiting 72 hours for minor performance before trying some different config values Yes, I did a basic grid search for 24 hours. Could probably tune the Anxiety is high today reduce the stigma remember bear retro shirt it is in the first place but hyperparameters better, but I needed to show progress. Long story short BERT and variants have terrible tokenization and embeddings for my specific domain (which may as well be it’s own language for the information I’m interested in). I spent several weeks training BERT variants, but could never get > 70% classification accuracy without catastrophic forgetting (at which point, might as well just train a randomly initialized transformer). A smaller custom transformer with a custom vocabulary with normal initialization achieved 80% accuracy in barely any more time, so I decided to train a model from scratch for this domain. Might I ask why you’re making a LM from scratch instead of using an already well established one, or a clone of it?