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README.md
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# NT5, a T5 model trained to perform numerical reasoning
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T5-small model pre-trained on and fine-tuned on DROP. It was introduced in the paper [NT5?! Training T5 to Perform Numerical Reasoning](https://arxiv.org/abs/2104.07307) by Yang et al. and first released in [this repository](https://github.com/lesterpjy/numeric-t5). As the original implementation was in Tensorflow 2, I've converted the weigths to PyTorch. This model corresponds to RC Experiment 1 (see the paper), their best performing model.
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Disclaimer: The team releasing NT5 did not write a model card for this model so this model card has been written by me.
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@@ -99,6 +99,6 @@ This model achieves an F1 score of 0.7031 and exact match of 0.6687 on the devel
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biburl = {https://dblp.org/rec/journals/corr/abs-1903-00161.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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a service of Schloss Dagstuhl - Leibniz Center for Informatics
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```
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# NT5, a T5 model trained to perform numerical reasoning
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T5-small model pre-trained on 3 million (partly synthetic) texts and fine-tuned on DROP. It was introduced in the paper [NT5?! Training T5 to Perform Numerical Reasoning](https://arxiv.org/abs/2104.07307) by Yang et al. and first released in [this repository](https://github.com/lesterpjy/numeric-t5). As the original implementation was in Tensorflow 2, I've converted the weigths to PyTorch. This model corresponds to RC Experiment 1 (see the paper), their best performing model.
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Disclaimer: The team releasing NT5 did not write a model card for this model so this model card has been written by me.
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biburl = {https://dblp.org/rec/journals/corr/abs-1903-00161.bib},
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bibsource = {dblp computer science bibliography, https://dblp.org}
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}
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a service of Schloss Dagstuhl - Leibniz Center for Informatics\thomebrowsesearchabout
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```
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