Add license terms and usage disclaimers

README.md

@@ -1,5 +1,6 @@
 ---
 language: "en"
+license: cc-by-nc-sa-4.0
 tags:
 - financial-sentiment-analysis
 - sentiment-analysis
@@ -7,6 +8,59 @@ widget:
 - text: "Stocks rallied and the British pound gained."
 ---
 
+# FinBERT
+
+## 📜 License and Usage Terms
+
+### Model Weights License
+The FinBERT model weights are made available under **CC BY-NC-SA 4.0** 
+(Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International).
+
+**This license restricts commercial use.** You may use this model for 
+non-commercial purposes only, and any adaptations must be shared under 
+the same license.
+
+### Training Data Attribution
+This model was trained using the **Financial PhraseBank** dataset:
+
+> Malo, P., Sinha, A., Korhonen, P., Wallenius, J., & Takala, P. 
+> (2014). Good debt or bad debt: Detecting semantic orientations in 
+> economic texts. *Journal of the Association for Information Science 
+> and Technology*, 65(4), 782-796.
+
+The Financial PhraseBank dataset is licensed under **CC BY-NC-SA 3.0**.
+
+The underlying language model was further pre-trained on a subset of the 
+Reuters TRC2 corpus, which is distributed by NIST under its own access terms.
+
+## ⚠️ User Responsibilities
+
+**You are solely responsible for**:
+- Ensuring your use complies with the CC BY-NC-SA 4.0 license
+- Obtaining any necessary rights clearances for your specific use case
+- Determining whether your intended use qualifies as "non-commercial"
+- Compliance with any applicable laws and regulations
+
+**Prosus makes no representation** that any particular use is permitted 
+and does not grant rights in third-party training data.
+
+## 🚫 Disclaimer
+
+**NO WARRANTY**: This model is provided "AS IS" without warranty of any 
+kind, express or implied, including but not limited to warranties of 
+merchantability, fitness for a particular purpose, or non-infringement.
+
+**NOT AN OFFICIAL PRODUCT**: This is not an official Prosus product. 
+It was created as part of a research project.
+
+**NO SUPPORT**: Prosus does not provide support, maintenance, or updates 
+for this model.
+
+**LIABILITY**: In no event shall MIH AI B.V. or Prosus be liable for any 
+claim, damages, or other liability arising from the use of this model.
+
+## Model Description
+
 FinBERT is a pre-trained NLP model to analyze sentiment of financial text. It is built by further training the BERT language model in the finance domain, using a large financial corpus and thereby fine-tuning it for financial sentiment classification. [Financial PhraseBank](https://www.researchgate.net/publication/251231107_Good_Debt_or_Bad_Debt_Detecting_Semantic_Orientations_in_Economic_Texts) by Malo et al. (2014) is used for fine-tuning. For more details, please see the paper [FinBERT: Financial Sentiment Analysis with Pre-trained Language Models](https://arxiv.org/abs/1908.10063) and our related [blog post](https://medium.com/prosus-ai-tech-blog/finbert-financial-sentiment-analysis-with-bert-b277a3607101) on Medium.
 
 The model will give softmax outputs for three labels: positive, negative or neutral.
@@ -17,6 +71,11 @@ About Prosus
 
 Prosus is a global consumer internet group and one of the largest technology investors in the world. Operating and investing globally in markets with long-term growth potential, Prosus builds leading consumer internet companies that empower people and enrich communities. For more information, please visit www.prosus.com.
 
-Contact information
+## 📧 Contact
+
+For questions about this research project:
+- Dogu Araci: dogu.araci[at]prosus.com
+- Zulkuf Genc: zulkuf.genc[at]prosus.com
 
-Please contact Dogu Araci dogu.araci[at]prosus[dot]com and Zulkuf Genc zulkuf.genc[at]prosus[dot]com about any FinBERT related issues and questions.
+**Note**: Questions about commercial licensing or legal permissions 
+cannot be addressed by the research team. See the License section above.