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---
license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) object mass version 17
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.
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