April 23, 2024, 4:43 a.m. | Mitodru Niyogi, Arnab Bhattacharya

cs.LG updates on arXiv.org arxiv.org

arXiv:2404.14395v1 Announce Type: cross
Abstract: In this paper, we present Paramanu-Ganita, a 208 million parameter novel Auto Regressive (AR) decoder based language model on mathematics. The model is pretrained from scratch at context size of 4096 on our curated mixed mathematical corpus. We evaluate our model on both perplexity metric and GSM8k mathematical benchmark. Paramanu-Ganita despite being 35 times smaller than 7B LLMs, outperformed generalist LLMs such as LLaMa-1 7B by 28.4% points, LLaMa-2 7B by 27.6% points, Falcon 7B …

abstract arxiv auto benchmark capabilities context cs.ai cs.cl cs.lg decoder language language model mathematics mixed novel paper perplexity scratch type

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