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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-large-patch16-224-pt22k-ft22k |
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tags: |
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- generated_from_trainer |
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metrics: |
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- pearsonr |
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- r_squared |
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model-index: |
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- name: motes_mtci_microsoft-beit-large-patch16-224-pt22k-ft22k |
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results: [] |
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--- |
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# Ocsai-D Large |
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This model is a trained model for scoring creativity - specifically figural (drawing-based) originality scoring. It is a fine-tuned version of [beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224-pt22k-ft22k). |
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It achieves the following results on the evaluation set: |
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- Mse: 0.0067 |
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- Pearsonr: 0.85 |
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- R2: 0.63 |
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- Rmse: 0.082 |
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It can be tried at <https://openscoring.du.edu/draw>. |
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## Model description |
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See the pre-print: |
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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 |
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*^Authors contributed equally.* |
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## Intended uses & limitations |
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This model judges the originality of figural drawings. There are some limitations. |
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First, there is a confound with elaboration - drawing more leads - partially - to higher originality. |
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Secondly, the training is specific to one test, and mileage may vary on other images. |
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## Training and evaluation data |
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This is trained on the Multi-Trial Creative Ideation task (MTCI; [Barbot 2018](https://pubmed.ncbi.nlm.nih.gov/30618952/)), with the [data](https://osf.io/kqn9v/) from Patterson et al. ([2023](https://doi.org/10.31234/osf.io/t63dm)). |
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The train/test splits aligned with the ones from Patterson et al. 2023. |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
