task_categories:image-to-text task_categories:text-to-image language:en license:mit size_categories:100K<n<1M format:json modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
license: mit
task_categories:
- image-to-text
- text-to-image
language:
- en
pretty_name: simons ARC (abstraction & reasoning corpus) task version 11
size_categories:
- 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data.jsonl
---

# Version 1

Have dataset items that are somewhat evenly of each type. The LLM validation loss went down and then continue to rise afterwards,
so I guess the complexity of the dataset was too high.
The image sizes are between 1 and 10 pixels.

# Version 2

Here the majority of dataset items are histograms. 
Smaller images. Here the image sizes are between 1 and 5 pixels.
Let's see if the LLM does better on this one.

# Version 3

Focus on pair comparisons finding color intersection and color union.

# Version 4

image size 3-10.
This converged slowly. I suspect the bigger image size was too optimistic. Next time try with a smaller image size.

# Version 5

image size 3-8.
Added `pair_histogram_add`, `pair_histogram_max`, `pair_histogram_min`.
This converged slowly. I suspect the big image size is still too optimistic. Next time try with an even smaller image size.

# Version 6

I'm trying even smaller images.

image width 1-5, this is what it has been trained on in the past.

image height 3-8, this is slightly bigger than what it has been trained on.

This did the LLM make sense of quite fast. Next I'm goint to try with a wider image.

# Version 7

image width 3-8, this is slightly bigger than what it has been trained on, and something that the model has struggled learning.

image height 1-5, this is what it has been trained on in the past.

# Version 8

image size 1-8.

I have been training on image pairs, so the model is now somewhat ok at making sense on image pairs.
So I hope it will be better at processing tasks, since a task is a list of image pairs.

# Version 9

image size 1-10.

same weight to all transformations.

Making use of TaskFormatterRLECompact` for the first time.
Oh, the number of tokens per row is too high. I'm going to use smaller images.

# Version 10

image size 1-5.

same weight to all transformations.

Making use of TaskFormatterRLECompact`.

# Version 11

image size 1-5.

same weight to all transformations.

Making use of TaskFormatterRLECompact`.
