arXiv Computation and Language By Sait Furkan Teke (ufak AI)

ufakzeka-1: Building and Evaluating a 151M-Parameter Turkish Language Model from Scratch

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The paper introduces ufakzeka-1, a 151‑million‑parameter Turkish language model trained from scratch on 13.5 B tokens. It details the tokenizer, a three‑stage pretraining schedule, post‑training data augmentation, and a comprehensive evaluation suite that includes release gates, a rule‑checked conversation sweep, and hand tests—all with prompts excluded from training data. The authors report three key findings about safety gate performance, training‑seed variance, and data‑round effects, and they release the model weights, data recipe, evaluation code, and spend ledger under Apache‑2.0.

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