Pretrained from scratch using GPT-2 architecture and a dataset of Latin texts (Corpus Corporum) 64 token context, loss 4.5, trained on 1 epoch of 492 million tokens GPT2 style tokenizer trained with min_frequency of 2000
Tends to get repetitive and is not very coherent, due to size and limited data.
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