This model was trained on a dataset I obtained from an online novel site. Please be aware that the stories (training data) might contain inappropriate content. This model is intended for research purposes only. The base model can be found here, which was obtained by patching a GPT2 Chinese model and its tokenizer with Cantonese characters. Refer to the base model for info on the patching process. Besides language modeling, another aim of this experiment was to test the accelerate library by offloading certain workloads to CPU as well as finding the optimal training iterations. The perplexity of this model is 16.12 after 400,000 steps. Comparing to the previous attempt 27.02 after 400,000 steps. It took around the same time duration to train this model but I only used 1 GPU here. The model was trained for 400,000 steps on 1 NVIDIA Quadro RTX6000 for around 30 hours at the Research Computing Services of Imperial College London. — Transformers 4.26.0.dev0 — Pytorch 1.13.1 — Datasets 2.8.0 — Tokenizers 0.13.2
Модальности:
Генерация текста
Задача: Генерация текста
Автор: jed351
Теги: gpt2, generated_from_trainer, model-index, text-generation-inference, endpoints_compatible
Лайков: 2 | Загрузок: 42
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
