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README.md
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---
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license: mit
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| 1 |
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---
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license: mit
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task_categories:
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- image-to-text
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- text-to-image
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language:
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- en
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pretty_name: simons ARC (abstraction & reasoning corpus) object mass version 21
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size_categories:
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- 10K<n<100K
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data.jsonl
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---
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# Version 1
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Measure the mass of objects for `pixel connectivity 4` and `pixel connectivity 8`.
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image size: 1-10.
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max_mass: 4.
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# Version 2
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image size: 1-20.
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max_mass: 5.
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This converged too slowly. I was too optimistic. I will have to proceed slower.
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# Version 3
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image size: 1-12.
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max_mass: 5.
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Too big spikes in the training loss. I will have to lower the `max_mass`, and gradually increase it.
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# Version 4
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image size: 1-15.
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max_mass: 2.
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The validation loss for this is fine. I'm increasing the `max_mass`.
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# Version 5
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image size: 1-20.
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max_mass: 3.
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# Version 6
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image size: 1-25.
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max_mass: 4.
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# Version 7
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image size: 1-30.
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max_mass: 2.
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# Version 8
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image size: 1-30.
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max_mass: 7.
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# Version 9
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image size: 1-30.
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max_mass: 8.
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# Version 10
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image size: 1-30.
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max_mass: 9.
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# Version 11
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image size: 1-30.
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max_mass: 10.
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# Version 12
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image size: 1-30.
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max_mass: 11.
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# Version 13
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image size: 1-30.
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max_mass: 15.
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# Version 14
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image size: 1-30.
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max_mass: 20.
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# Version 15
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image size: 1-30.
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max_mass: 25.
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# Version 16
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Added `PixelConnectivity.CORNER4`, so it can identify diagonal structures.
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image size: 1-10.
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max_mass: 5.
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# Version 17
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image size: 1-15.
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max_mass: 10.
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# Version 18
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Added mulple new `PixelConnectivity` modes: `LR2`, `TB2`, `TLBR2`, `TRBL2`, so it can identify line structures.
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image size: 1-10.
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max_mass: 5.
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# Version 19
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image size: 1-15.
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max_mass: 10.
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# Version 20
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Disabled `NEAREST4`, `ALL8`, `CORNER4`. So the model can be trained only on line structures.
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image size: 1-20.
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max_mass: 15.
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The model struggles with these settings. I have to lower the settings.
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# Version 21
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Still with disabled `NEAREST4`, `ALL8`, `CORNER4`. So the model can be trained only on line structures.
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Lowered the settings.
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image size: 1-10.
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max_mass: 6.
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