paper on weak-to-strong generalization.

openai's implementation of weak-to-strong learning setup for binary classification tasks.

The main script of the project is train_weak_to_strong.py. It can be run from the command line using the following command:

python train_weak_to_strong.py

The script accepts several command-line arguments to customize the training process. Here are some examples:

python train_weak_to_strong.py --batch_size 32 --max_ctx 512 --ds_name "sciq" --loss "logconf" --n_docs 1000 --n_test_docs 100 --weak_model_size "gpt2-medium" --strong_model_size "gpt2-large" --seed 42

• add pythia-configs
• try some chessy experiment
• plot scaling laws