Wesley Morris
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README.md
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results: []
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#
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on a dataset consisting of 4,620 summaries,
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scored on an analytic rubric by expert raters. This model predicts the raw score for Language Beyond the Source. The rubric is as follows:
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- Rmse: 0.4220
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- R2: 0.6236
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## Model description
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More information needed
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## Intended uses & limitations
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This model is intended to be used to provide feedback to users of iTELL, a framework for generating intelligent educational texts.
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here: [](https://www.youtube.com/watch?v=YZXVQjSDZtI)
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## Training and evaluation data
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Seventy summaries in the training set had Language Beyond the Source scores of <1, which is outside of the rubric.
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## Training procedure
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results: []
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# Language Beyond the Source
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## Model description
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This model is a fine-tuned version of [microsoft/deberta-v3-large](https://huggingface.co/microsoft/deberta-v3-large) on a dataset consisting of 4,620 summaries,
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scored on an analytic rubric by expert raters. This model predicts the raw score for Language Beyond the Source. The rubric is as follows:
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- Rmse: 0.4220
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- R2: 0.6236
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## Intended uses & limitations
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This model is intended to be used to provide feedback to users of iTELL, a framework for generating intelligent educational texts.
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For more information about iTELL, watch our video here: [](https://www.youtube.com/watch?v=YZXVQjSDZtI)
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## Training and evaluation data
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Seventy summaries in the training set had Language Beyond the Source scores of <1, which is outside of the rubric.
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These summaries were removed from the training and test sets.
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## Training procedure
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