From fdce96c3960f5f544bd68c0f18cc5cd096ecbfb3 Mon Sep 17 00:00:00 2001 From: =?utf8?q?Fran=C3=A7ois=20Fleuret?= Date: Sun, 23 Jun 2024 09:06:29 +0200 Subject: [PATCH 1/1] Update. --- README.txt | 6 +++--- tasks.py | 4 ++-- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/README.txt b/README.txt index d5cf6d8..4a5ca30 100644 --- a/README.txt +++ b/README.txt @@ -38,12 +38,12 @@ My home-baked GPT-37M trained with 250k solves this with ~99% success At every iteration, we select the GPT with the lowest test accuracy, and run one epoch. +* Creating new quizzes + If its test accuracy got higher than 97.5%, it will create new quizzes. To do so, it generates a large number of pairs of frames, and checks which ones of these quizzes are hard but not too hard, which -means - -[THIS IS THE IMPORTANT BIT]: +means [THIS IS THE IMPORTANT BIT]: it can be solved, in both time directions, by all the other GPTs **but one** diff --git a/tasks.py b/tasks.py index 1254323..ecf0a65 100755 --- a/tasks.py +++ b/tasks.py @@ -101,8 +101,8 @@ class World(Task): self.batch_size = batch_size self.device = device - self.height = 7 - self.width = 9 + self.height = 6 + self.width = 8 self.train_input = world.generate_seq( nb_train_samples, height=self.height, width=self.width -- 2.20.1