---
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.