jaxgmg2_3phase_optim_state_alpha1

Note: Einar trained these models and the description below is uncertain.

Single RL agent checkpoint from jaxgmg2_3phase_optim_state resumed with alpha changed from 0.6 to 1.0, exploring how changing the value function loss weight mid-training affects learning dynamics.

WandB: https://wandb.ai/devinterp/jaxgmg2_patt

Hyperparams

rl_action=train
alpha=1.0
discount_rate=0.98
lr=5e-05
num_total_env_steps=7372800000
num_rollout_steps=64
num_levels=9600
cheese_loc=any
env_layout=open
env_size=13
mask_type=first_episode
use_prev_action=False
grad_acc_per_chunk=4
log_optimizer_state=True
resume=jaxgmg2_3phase_optim_state/al_0.6_g_0.98_id_17_seed_980617
resume_id=3810
resume_optim=True
deterministic=True
seed=42
checkpoint=al_0.6_g_0.98_id_17_seed_980617_resume_alpha1
ckpt_dir=jaxgmg2_3phase_optim_state_alpha1
wandb_project=jaxgmg2_patt
use_wandb=True
use_hf=True

Naming Schema

Checkpoint: al_0.6_g_0.98_id_17_seed_980617_resume_alpha1

Reproduced with

See train.yaml in this repository. Run from the timaeus monorepo.