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
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