Update README.md

README.md

@@ -12,23 +12,28 @@ pipeline_tag: text-classification
 tags:
 - medical
 model_description: >-
-  This is basically the German translation of arpanghoshal/EmoRoBERTa. We used
-  the go_emotions dataset, translated it into German and fine-tuned the
-  FacebookAI/xlm-roberta-base model. So this model allows the classification
-  of 28 emotions in German Transcripts ('admiration', 'amusement', 'anger',
+  This model was fine-tuned on the German translation of the go_emotions dataset.
+  It is designed to classify German text across 27 emotions (and a "neutral" category).
+  The model is fine-tuned on the FacebookAI/xlm-roberta-base model. 
+  It contains the following emotions: 'admiration', 'amusement', 'anger',
   'annoyance', 'approval', 'caring', 'confusion', 'curiosity', 'desire',
   'disappointment', 'disapproval', 'disgust', 'embarrassment', 'excitement',
   'fear', 'gratitude', 'grief', 'joy', 'love', 'nervousness', 'optimism',
   'pride', 'realization', 'relief', 'remorse', 'sadness', 'surprise',
-  'neutral'). A paper will be published soonish...
+  'neutral'. 
 ---
 # Model Card for German-Emotions
 
-This is basically the German translation of arpanghoshal/EmoRoBERTa. We used the go_emotions dataset, translated it into German and fine-tuned the FacebookAI/xlm-roberta-base model. So this model allows the classification of **28 emotions** in German Transcripts (**'admiration', 'amusement', 'anger', 'annoyance', 'approval', 'caring', 'confusion', 'curiosity', 'desire', 'disappointment', 'disapproval', 'disgust', 'embarrassment', 'excitement', 'fear', 'gratitude', 'grief', 'joy', 'love', 'nervousness', 'optimism', 'pride', 'realization', 'relief', 'remorse', 'sadness', 'surprise', 'neutral'**). See our published paper at the bottom for detailed information.
+# German-Emotions
+This model is designed to infer 27 emotions and a *neutral* category from German text. It is a fine-tuned version of **FacebookAI/xlm-roberta-base**, trained on the **German translation** of the [GoEmotions dataset](https://huggingface.co/datasets/google-research-datasets/go_emotions). 
 
+The original GoEmotions dataset contains 53.4k English Reddit comments labeled with one or more emotions. For this model, the data was translated into German and used to fine-tune the multilingual XLM-RoBERTa base model (270M parameters), which was pretrained on 2.5TB of CommonCrawl data across 100 languages, including German.
 
-## Model Details
+For additional information, please see the reference at the bottom of this page. 
+### Supported Emotion Labels
+*admiration*, *amusement*, *anger*, *annoyance*, *approval*, *caring*, *confusion*, *curiosity*, *desire*, *disappointment*, *disapproval*, *disgust*, *embarrassment*, *excitement*, *fear*, *gratitude*, *grief*, *joy*, *love*, *nervousness*, *optimism*, *pride*, *realization*, *relief*, *remorse*, *sadness*, *surprise*, *neutral*
 
+## Model Details
 
 - **Model type:** text-classification
 - **Language(s) (NLP):** German
@@ -43,7 +48,6 @@ This is basically the German translation of arpanghoshal/EmoRoBERTa. We used the
     - f1: 0.45
     - kappa: 0.42
 ---
-
 ## Classification Metrics
 
 | Emotion                 | Sentiment   | F1   | Cohen’s Kappa |