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wesleymorris
/
longformer-content-global

Text Classification
Transformers
PyTorch
English
longformer
macroeconomics
automated summary evaluation
content
Model card Files
xet
Community
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Wesley Morris commited on
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Update README.md

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@@ -43,9 +43,11 @@ The following diagram illustrates the model architecture:
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  ![model diagram](model_diagram.png)
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  When providing input to the model, the summary and the source should be concatenated using the seperator token \</s>.
 
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  This allows the model to have access to both the summary and the source to provide more accurate scores. The model reported an R2 of 0.82 on the test set of summaries.
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  ![content scatter](content_scatter.png)
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  ## Contact
 
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  For questions or comments about this model, please contact [wesley.g.morris@vanderbilt.edu](wesley.g.morris@vanderbilt.edu).
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  ---
 
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  ![model diagram](model_diagram.png)
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  When providing input to the model, the summary and the source should be concatenated using the seperator token \</s>.
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+ All summaries for 15 sources were withheld from the training set to use for testing.
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  This allows the model to have access to both the summary and the source to provide more accurate scores. The model reported an R2 of 0.82 on the test set of summaries.
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  ![content scatter](content_scatter.png)
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  ## Contact
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+ This model was developed by LEAR Lab at Vanderbilt University.
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  For questions or comments about this model, please contact [wesley.g.morris@vanderbilt.edu](wesley.g.morris@vanderbilt.edu).
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  ---