language: en
tags:
- GPT-2
datasets:
- imdb
widget:
- text: 'I think the movie was '
license: mit
GPT2-IMDB-neutral (LM + RL) 🎞😐✍
What is it?
A small GPT2 (lvwerra/gpt2-imdb) language model fine-tuned to produce neutral-ish movie reviews based on the IMDB dataset. The model is trained with rewards from a BERT sentiment classifier (lvwerra/gpt2-imdb) via PPO.
Why?
After reproducing the experiment lvwerra/gpt2-imdb-pos but for generating negative movie reviews (mrm8488/gpt2-imdb-neg) I wanted to check if I could generate neutral-ish movie reviews. So, based on the classifier output (logit), I saw that clearly negative reviews gives around -4 values and clearly positive reviews around 4. Then, it was esay to establish an interval [-1.75,1.75] that it could be considered as neutral. So if the classifier output was in that interval I gave it a positive reward while values out of the interval got a negative reward.
Training setting
The model was trained for 100 optimisation steps with a batch size of 128 which corresponds to 30000 training samples. The full experiment setup (for positive samples) in trl repo.
Examples
A few examples of the model response to a query before and after optimisation:
| query | response (before) | response (after) | rewards (before) | rewards (after) |
|---|---|---|---|---|
| Okay, my title is | partly over, but this drama still makes me proud to read its first 40... | weird. The title is "mana were, ahunter". "Man... | 4.200727 | -1.891443 |
| Where is it written that | there is a monster in this movie anyway? How is it that the entire | [ of the women in the recent women of jungle business between Gender and husband | -3.113942 | -1.944993 |
| As a lesbian, I | cannot believe I was in the Sixties! Subtle yet witty, with original | found it hard to get responsive. In fact I found myself with the long | \t3.906178 | \t0.769166 |
| The Derek's have over | three times as many acting hours than Jack Nicholson? You think bitches? | 30 dueling characters and kill of, they retreat themselves to their base. | -2.503655 | -1.898380 |
All credits to @lvwerra
Created by Manuel Romero/@mrm8488
Made with ♥ in Spain