abhishekraok/proposer-basicfns-opt125m-sft2k

A PBE task proposer model. Model that generates a random sequence of functions that will transform given inputs to outputs. We start with the pre-trained OPT 125M model, then finetune on a random list of functions. This can be later be optimized using RL. The SFT training ensures that the model starts with a good baseline for future RL training. The model is trained to output a valid list of functions from the common_functions.py file.

We measure accuracy, ratio of valid tasks generated. When evaluated using this gives the result of

python wandering_light/evals/evaluate_proposer.py --model abhishekraok/proposer-basicfns-opt125m-sft2k --solver-model abhishekraok/induction-basicfns-opt125m-longsft
EvalResult(parse_rate=0.96, avg_function_count=2.02, avg_function_count_ratio=1.38, solver_success_rate=0.15, num_samples=100, frac_non_zero_std=0.31)

See the wandering-light repo for more details.