Testing a QLoRA adaptor for allenai/MolmoE-1B-0924,
Targets top 10 experts that are activated when pointing is involved and image pooling and projection layers of Vision backbone
Trained on 47 screenshots of a low-poly video game with ragdoll casualties
Evaluated on 44 screenshots of aforementioned video game
Molmo has an edge case where it declares there are no humans in an image:
This custom QLoRA successfully reduces the occurance of these cases
However, pointing to non-human objects is observed to increase.
Comparison of Model performance with and without QLora on Eval dataset
| Model | MolmoE-1B | MolmoE-1B w/ QLora |
|---|---|---|
| Precision | 82.4 | 81.5 |
| Recall | 63.5 | 72.1 |
Dataset: reubk/RavenfieldDataset
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