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Sponsored by
APIMaster
tiedaar / short-answer-classification
Model's Last Updated: July 03 2024
text-classification
Introduction of short-answer-classification
Model Details of short-answer-classification
Short Answer Classification Model
This is a finetuned MPnet model with a classification head designed to predict whether a short answer is correct.
Training
This model was trained on the MultiRC dataset, a corpus of 20,422 answers to 5,130 questions about 456 source texts. Before training, chatGPT was used to generate correct answers to each question given the source. This was used as the reference answer. The model takes the reference answer together with the target answer and predicts whether the target answer is correct. 15% of sources along with all of their questions and answers were withheld from the training data and used to evaluate the model. The model had an F1 of 0.81 on the test set.
Input sequences to the model should follow this pattern:
{target_answer} </s> {reference_answer}
Contact
This model was developed by LEAR Lab at Vanderbilt University. For questions or comments about this model, please contact [email protected] .
Runs of tiedaar short-answer-classification on huggingface.co
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More Information About short-answer-classification huggingface.co Model
Url of short-answer-classification
short-answer-classification huggingface.co Url
Provider of short-answer-classification huggingface.co
Other API from tiedaar
Updated:November 28 2022
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