Edit model card

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
Downloads last month
7
Safetensors
Model size
85.8M params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for POrg/ocsai-d-base

Finetuned
(60)
this model