Update README.md

README.md

@@ -9,4 +9,56 @@ base_model:
 pipeline_tag: text-classification
 tags:
 - sentiment
----
+---
+
+# Latvian Twitter Sentiment Analysis
+
+This is a BERT-base model trained on ~26,000 manually annotated tweets in Latvian from various sources for sentiment analysis. 
+
+
+<b>Labels</b>: 
+0 -> Neutral;
+1 -> Positive;
+2 -> Negative.
+
+This sentiment analysis model has been integrated in [this HF Space](https://huggingface.co/spaces/matiss/Latvian-Twitter-Sentiment-Analysis).
+
+## Example Pipeline
+```python
+from transformers import pipeline
+model_path = "matiss/Latvian-Twitter-Sentiment-Analysis"
+sentiment_task = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
+sentiment_task("Man garšo pankūkas ar kotletēm")
+```
+```
+[{'label': 'Positive', 'score': 0.9032208919525146}]
+```
+
+
+
+## Corpora Used for Training
+---------
+* [Twitēdiens](https://huggingface.co/datasets/matiss/Latvian-Twitter-Eater-Corpus-Sentiment) - the Latvian Twitter Eater Corpus of ~5000 manually annotated food-related tweets.
+* [Pinnis](https://github.com/pmarcis/latvian-tweet-corpus) - ~ 7000 tweets from politicians and companies
+* [Peisenieks](https://github.com/FnTm/latvian-tweet-sentiment-corpus) - ~ 1000 general tweets with sentiment annotated by multiple annotators
+* [Vīksna](https://github.com/RinaldsViksna/sikzinu_analize) - ~ 4000 general tweets
+* [Nicemanis](https://github.com/nicemanis/LV-twitter-sentiment-corpus) - ~ 2000 general tweets
+* [Špats](https://github.com/gatis/om) - ~ 6000 general tweets
+
+
+Publications
+---------
+
+If you use this corpus or scripts, please cite the following paper:
+
+Uga Sproģis and Matīss Rikters (2020). "[What Can We Learn From Almost a Decade of Food Tweets.](https://arxiv.org/abs/2007.05194)" In Proceedings of the 9th Conference Human Language Technologies - The Baltic Perspective ([Baltic HLT 2020](https://klc.vdu.lt/hlt/programme)) (2020).
+
+```bibtex
+@inproceedings{SprogisRikters2020BalticHLT,
+	author = {Sproģis, Uga and Rikters, Matīss},
+	booktitle={In Proceedings of the 9th Conference Human Language Technologies - The Baltic Perspective (Baltic HLT 2020)},
+	title = {{What Can We Learn From Almost a Decade of Food Tweets}},
+	address={Kaunas, Lithuania},
+	year = {2020}
+}
+```