From a66db7d8284a41c6b4b8319ea3883da6ffd5d625 Mon Sep 17 00:00:00 2001 From: Stefan Engl Date: Thu, 3 Sep 2020 15:23:42 +0200 Subject: [PATCH] Corrected link to paper (#6905) --- model_cards/oliverguhr/german-sentiment-bert/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/model_cards/oliverguhr/german-sentiment-bert/README.md b/model_cards/oliverguhr/german-sentiment-bert/README.md index 2594aacab5..a8e03e278f 100644 --- a/model_cards/oliverguhr/german-sentiment-bert/README.md +++ b/model_cards/oliverguhr/german-sentiment-bert/README.md @@ -4,7 +4,7 @@ This model was trained for sentiment classification of German language texts. To we provide a Python package that bundles the code need for the preprocessing and inferencing. The model uses the Googles Bert architecture and was trained on 1.834 million German-language samples. The training data contains texts from various domains like Twitter, Facebook and movie, app and hotel reviews. -You can find more information about the dataset and the training process in the [paper](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.201.pdf). +You can find more information about the dataset and the training process in the [paper](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.202.pdf). ## Using the Python package