# GPT2-IMDB-neg (LM + RL) ๐ŸŽž๐Ÿ˜กโœ All credits to [@lvwerra](https://twitter.com/lvwerra) ## What is it? A small GPT2 (`lvwerra/gpt2-imdb`) language model fine-tuned to produce **negative** movie reviews based the [IMDB dataset](https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews). The model is trained with rewards from a BERT sentiment classifier (`lvwerra/gpt2-imdb`) via **PPO**. ## Why? I wanted to reproduce the experiment [lvwerra/gpt2-imdb-pos](https://huggingface.co/lvwerra/gpt2-imdb-pos) but for generating **negative** movie reviews. ## 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 (for positive samples) in [trl repo](https://lvwerra.github.io/trl/04-gpt2-sentiment-ppo-training/). ## Examples 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| ## Training logs and metrics Watch the whole training logs and metrics on [W&B](https://app.wandb.ai/mrm8488/gpt2-sentiment-negative?workspace=user-mrm8488) > Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488) > Made with in Spain