POrg/ocsai-d-base

Ocsai-D Base

This model is a trained model for scoring creativity - specifically figural (drawing-based) originality scoring. It is a fine-tuned version of beit-base-patch16-224. It achieves the following results on the evaluation set:

• Mse: 0.0077
• Pearsonr: 0.82
• R2: 0.52
• Rmse: 0.088

It can be tried at https://openscoring.du.edu/draw.

Model description

See the pre-print:

Acar, S.^, Organisciak, P.^, & Dumas, D. (2023). Automated Scoring of Figural Tests of Creativity with Computer Vision. http://dx.doi.org/10.13140/RG.2.2.26865.25444

^Authors contributed equally.

Intended uses & limitations

This model judges the originality of figural drawings. There are some limitations.

First, there is a confound with elaboration - drawing more leads - partially - to higher originality.

Secondly, the training is specific to one test, and mileage may vary on other images.

Training and evaluation data

This is trained on the Multi-Trial Creative Ideation task (MTCI; Barbot 2018), with the data from Patterson et al. (2023).

The train/test splits aligned with the ones from Patterson et al. 2023.

Framework versions

• Transformers 4.40.0
• Pytorch 2.2.1+cu121
• Datasets 2.19.0
• Tokenizers 0.19.1