license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) object mass version 19
size_categories:
- 10K<n<100K
configs:
- config_name: default
data_files:
- split: train
path: data.jsonl
Version 1
Measure the mass of objects for pixel connectivity 4 and pixel connectivity 8.
image size: 1-10.
max_mass: 4.
Version 2
image size: 1-20.
max_mass: 5.
This converged too slowly. I was too optimistic. I will have to proceed slower.
Version 3
image size: 1-12.
max_mass: 5.
Too big spikes in the training loss. I will have to lower the max_mass, and gradually increase it.
Version 4
image size: 1-15.
max_mass: 2.
The validation loss for this is fine. I'm increasing the max_mass.
Version 5
image size: 1-20.
max_mass: 3.
Version 6
image size: 1-25.
max_mass: 4.
Version 7
image size: 1-30.
max_mass: 2.
Version 8
image size: 1-30.
max_mass: 7.
Version 9
image size: 1-30.
max_mass: 8.
Version 10
image size: 1-30.
max_mass: 9.
Version 11
image size: 1-30.
max_mass: 10.
Version 12
image size: 1-30.
max_mass: 11.
Version 13
image size: 1-30.
max_mass: 15.
Version 14
image size: 1-30.
max_mass: 20.
Version 15
image size: 1-30.
max_mass: 25.
Version 16
Added PixelConnectivity.CORNER4, so it can identify diagonal structures.
image size: 1-10.
max_mass: 5.
Version 17
image size: 1-15.
max_mass: 10.
Version 18
Added mulple new PixelConnectivity modes: LR2, TB2, TLBR2, TRBL2, so it can identify line structures.
image size: 1-10.
max_mass: 5.
Version 19
image size: 1-15.
max_mass: 10.