How to use this model directly from the
tokenizer = AutoTokenizer.from_pretrained("mrm8488/gpt2-imdb-neg") model = AutoModelWithLMHead.from_pretrained("mrm8488/gpt2-imdb-neg")
All credits to @lvwerra
A small GPT2 (
lvwerra/gpt2-imdb) language model fine-tuned to produce negative movie reviews based the IMDB dataset. The model is trained with rewards from a BERT sentiment classifier (
lvwerra/gpt2-imdb) via PPO.
I wanted to reproduce the experiment lvwerra/gpt2-imdb-pos but for generating negative movie reviews.
The model was trained for
100 optimisation steps with a batch size of
256 which corresponds to
25600 training samples. The full experiment setup (for positive samples) in 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)|
|This movie is a fine||attempt as far as live action is concerned, n...||example of how bad Hollywood in theatrics pla...||2.118391||-3.31625|
|I have watched 3 episodes||with this guy and he is such a talented actor...||but the show is just plain awful and there ne...||2.681171||-4.512792|
|We know that firefighters and||police officers are forced to become populari...||other chains have going to get this disaster ...||1.367811||-3.34017|
Watch the whole training logs and metrics on W&B
Created by Manuel Romero/@mrm8488
Made with ♥ in Spain