UAlbertaUAIS
/

Chelberta

@@ -1,202 +1,123 @@
 ---
 library_name: peft
 base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
 ---
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 ### Framework versions

 ---
 library_name: peft
 base_model: cardiffnlp/twitter-roberta-base-sentiment-latest
+license: mit
+language:
+- en
+metrics:
+- accuracy
+pipeline_tag: text-classification
+tags:
+- NHL
+- Hockey
+- Sports
+- roberta
+- sentiment analysis
 ---
+# Chelberta
+This is a finetuned model of [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest) trained on
+5168 sentiment labelled reddit comments from subreddits of NHL hockey teams in December 2023. This model is suitable for English.
+<b>Labels</b>:
+0 -> Negative;
+1 -> Neutral;
+2 -> Positive
+This sentiment analysis has been used for the [NHL Positivity Index](https://uais.dev/projects/nhl-positivity-index/)
+The full dataset can be found [here](https://www.kaggle.com/datasets/jacobwinch/nhl-reddit-comments)
+## Example Pipeline
+```python
+from transformers import pipeline, AutoModelForSequenceClassification, AutoTokenizer
+from peft import PeftModel
+import torch
+model_id = 'cardiffnlp/twitter-roberta-base-sentiment-latest'
+peft_model_id = 'UAlbertaUAIS/Chelberta'
+model = AutoModelForSequenceClassification.from_pretrained(model_id, num_labels=3)
+tokenizer = AutoTokenizer.from_pretrained(model_id, max_length=512)
+model = PeftModel.from_pretrained(model, peft_model_id)
+model = model.merge_and_unload()
+classifier = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer, max_length = 512, truncation=True, device=0)
+classifier("Connor McDavid is good at hockey!")
+```
+[{'label': 'positive', 'score': 0.9888942837715149}]
+```
+- **Developed by:** The Unversity of Alberta Undergraduate Artificial Intelligence Society Student Group
+- **Model type:** roberta based
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Finetuned from model [optional]:** [cardiffnlp/twitter-roberta-base-sentiment-latest](https://huggingface.co/cardiffnlp/twitter-roberta-base-sentiment-latest)
+- **Repository:** https://github.com/UndergraduateArtificialIntelligenceClub/NHL-Positivity-Index
 ## Uses
+Chelberta is inteded to be used to analysis the sentiment of sports fans on social media.
 ## Evaluation
+Chelberta was evaluated on a testing dataset of 1000 human labelled NHL Reddit comments from December 2023, the testing set can be found [here](https://github.com/UndergraduateArtificialIntelligenceClub/NHL-Positivity-Index/blob/main/data/training_data/NHL-SentiComments-1K-TEST.json).
+The model had an 81.4% accuracy score.
+### References
+```
+@inproceedings{camacho-collados-etal-2022-tweetnlp,
+    title = "{T}weet{NLP}: Cutting-Edge Natural Language Processing for Social Media",
+    author = "Camacho-collados, Jose  and
+      Rezaee, Kiamehr  and
+      Riahi, Talayeh  and
+      Ushio, Asahi  and
+      Loureiro, Daniel  and
+      Antypas, Dimosthenis  and
+      Boisson, Joanne  and
+      Espinosa Anke, Luis  and
+      Liu, Fangyu  and
+      Mart{\'\i}nez C{\'a}mara, Eugenio" and others,
+    booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
+    month = dec,
+    year = "2022",
+    address = "Abu Dhabi, UAE",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.emnlp-demos.5",
+    pages = "38--49"
+}
+```
+```
+@inproceedings{loureiro-etal-2022-timelms,
+    title = "{T}ime{LM}s: Diachronic Language Models from {T}witter",
+    author = "Loureiro, Daniel  and
+      Barbieri, Francesco  and
+      Neves, Leonardo  and
+      Espinosa Anke, Luis  and
+      Camacho-collados, Jose",
+    booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
+    month = may,
+    year = "2022",
+    address = "Dublin, Ireland",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2022.acl-demo.25",
+    doi = "10.18653/v1/2022.acl-demo.25",
+    pages = "251--260"
+}
+```
+## Citation
 **APA:**
+Winch, J., Munjal, T., Lau, H., Bradley, A., Monaghan, A., & Subedi, Y. (2023). NHL Positivity Index. Undergraduate Artificial Intelligence Society. https://uais.dev/projects/nhl-positivity-index/
 ### Framework versions