add README

README.md

@@ -0,0 +1,37 @@
+---
+language:
+- da
+tags:
+- bert
+- pytorch
+- sentiment
+- polarity
+license: CC-BY_4.0
+datasets:
+- Twitter Sentiment
+- Europarl Sentiment
+metrics:
+- f1
+---
+
+# Danish BERT Tone for sentiment polarity detection
+
+The BERT Tone model detects sentiment polarity (positive, neutral or negative) in Danish texts. 
+It has been finetuned on the pretrained Danish BERT model by BotXO. 
+
+See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-tone) for more details. 
+
+
+Here is how to use the model:
+
+```python
+from transformers import BertTokenizer, BertForSequenceClassification
+
+model = BertForSequenceClassification.from_pretrained("DaNLP/da-bert-tone-sentiment-polarity")
+tokenizer = BertTokenizer.from_pretrained("DaNLP/da-bert-tone-sentiment-polarity")
+```
+
+## Training data
+
+The data used for training come from the [Twitter Sentiment](https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#twitsent) and [EuroParl sentiment 2](https://danlp-alexandra.readthedocs.io/en/latest/docs/datasets.html#europarl-sentiment2) datasets.
+