up readme 4

README.md

@@ -48,19 +48,6 @@ Fine-tuned on a 2k sample of manually annotated Reddit (EN) and Twitter (PL) dat
 - **License:** [More Information Needed]
 - **Finetuned from model:** [cardiffnlp/twitter-xlm-roberta-base-sentiment](https://huggingface.co/cardiffnlp/twitter-xlm-roberta-base-sentiment)
 
-## Model Sources 
-
-- **Repository:** [Colab notebook](https://colab.research.google.com/drive/1Rqgjp2tlReZ-hOZz63jw9cIwcZmcL9lR?usp=sharing)
-- **Paper:** TBA
-- **BibTex citation:** 
-```
-@misc{SentimenTwGK2023,
-  author={Gajewska, Ewelina and Konat, Barbara},
-  title={SentimenTw XLM-RoBERTa-base Model for Multilingual Sentiment Classification on Social Media},
-  year={2023},
-  howpublished = {\url{https://huggingface.co/eevvgg/sentimenTw-political}},
-}
-```
 
 # Uses
 
@@ -84,6 +71,21 @@ labels = [i['label'] for i in result] # ['neutral', 'positive']
 
 ```
 
+
+## Model Sources 
+
+- **Repository:** [Colab notebook](https://colab.research.google.com/drive/1Rqgjp2tlReZ-hOZz63jw9cIwcZmcL9lR?usp=sharing)
+- **Paper:** TBA
+- **BibTex citation:** 
+```
+@misc{SentimenTwGK2023,
+  author={Gajewska, Ewelina and Konat, Barbara},
+  title={SentimenTw XLM-RoBERTa-base Model for Multilingual Sentiment Classification on Social Media},
+  year={2023},
+  howpublished = {\url{https://huggingface.co/eevvgg/sentimenTw-political}},
+}
+```
+
 # Training Details
 
 - Trained for 3 epochs, mini-batch size of 8.