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What is it?

A small GPT2 (lvwerra/gpt2-imdb) language model fine-tuned to produce positive movie reviews based the IMDB dataset. The model is trained with rewards from a BERT sentiment classifier (lvwerra/gpt2-imdb) via PPO.

Training setting

The model was trained for 100 optimisation steps with a batch size of 256 which corresponds to 25600 training samples. The full experiment setup can be found in the Jupyter notebook in the trl repo.


A few examples of the model response to a query before and after optimisation:

query response (before) response (after) rewards (before) rewards (after)
I'd never seen a heavier, woodier example of Victorian archite... film of this caliber, and I think it's wonder... 3.297736 4.158653
I love John's work but I actually have to write language as in w... and I hereby recommend this film. I am really... -1.904006 4.159198
I's a big struggle to see anyone who acts in that way. by Jim Th... , but overall I'm happy with the changes even ... -1.595925 2.651260
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