Update README.md

README.md

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 This model was trained for toxicity labeling. Label_1 means TOXIC, Label_0 means NOT TOXIC
 
-The model was fine-tuned based off the already existing sentiment classifier oliverguhr/german-sentiment-bert . The aforementioned classifier performed poorly (44% accuracy on my test sample), so I trained the current toxicity classifier. It was noted that the same performance achieved training on the https://huggingface.co/dbmdz/bert-base-german-cased
+The model was fine-tuned based off the already existing sentiment classifier oliverguhr/german-sentiment-bert . The aforementioned classifier performed poorly (44% accuracy on my test sample), so I trained the current toxicity classifier. It was noted that the same performance achieved training on the [dbmdz/bert-base-german-cased model](https://huggingface.co/dbmdz/bert-base-german-cased).
 
 The accuracy is 91% on the test split during training and 83% on a manually picked (and thus harder) sample of 200 sentences (100 label 1, 100 label 0) at the end of the training.