Create README.md

README.md

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+---
+license: mit
+language:
+- en
+metrics:
+- f1
+- accuracy
+base_model:
+- google-t5/t5-base
+library_name: transformers
+---
+# Computational Analysis of Communicative Acts for Understanding Crisis News Comment Discourses
+
+The official trained models for **"Computational Analysis of Communicative Acts for Understanding Crisis News Comment Discourses"**. 
+
+This model is based on **T5-base** and uses the **Compacter** ([Compacter: Efficient Low-Rank Adaptation for Transformer Models](https://arxiv.org/abs/2106.04647)) architecture. It has been fine-tuned on our **crisis narratives dataset**.
+
+---
+
+### Model Information
+
+- **Architecture:** T5-base with Compacter
+- **Task:** Single-label classification for communicative act actions
+- **Classes:**  
+  - `informing statement`  
+  - `challenge`  
+  - `rejection`  
+  - `appreciation`  
+  - `request`  
+  - `question`  
+  - `acceptance`  
+  - `apology`
+  - `evaluation`
+  - `proposal`
+  - `denial`
+  - `admission`
+
+---
+
+### How to Use the Model
+
+To use this model, you will need the original code from our paper, available here:  
+[Acts in Crisis Narratives - GitHub Repository](https://github.com/Aalto-CRAI-CIS/Acts-in-crisis-narratives/tree/main/few_shot_learning/AdapterModel)
+
+#### Steps to Load and Use the Fine-Tuned Model:
+
+1. Add your test task method to `seq2seq/data/task.py`, similar to other task methods.  
+2. Modify `adapter_inference.sh` to include your test task's information and this model's name, and then run it.  
+
+```bash
+--model_name_or_path CrisisNarratives/adapter-13classes-single_label
+```
+
+For detailed instructions, refer to the GitHub repository linked above.
+
+---
+
+### Citation
+
+If you use this model in your work, please cite:  
+
+##### TO BE ADDED.
+
+### Questions or Feedback?
+
+For questions or feedback, please reach out via our [contact form](mailto:[email protected]).
+
+
+