Update README.md

README.md

@@ -2,6 +2,7 @@
 license: cc-by-nc-nd-4.0
 metrics:
 - f1
+- accuracy
 base_model:
 - FacebookAI/xlm-roberta-base
 language:
@@ -24,13 +25,14 @@ tags:
 # Model Card for Model ID
 
 Classifies polarised gendered discourse for all indic languages.
+
 0=Neutral
 1=Sexist and misogynistic 
 2=Empowering
 
 ## Model Details
 
-Come back later at an unspecified date for further information
+genAMI, paper forthcoming
 
 ## Author Details
 
@@ -45,17 +47,17 @@ United Nations University - MERIT
 
 - **Developed by:** Praachi Kumar
 - **Model type:** Fine-tuned XLM-RoBERTa base for sequence classification
-- **Language(s) (NLP):** Multi Indic Languages
+- **Language(s) (NLP):** Multi, focus on Indic
 - **License:** Non commercial, no derrivatives
-- **Paper:** forthcoming
+- **Paper:** Gorthcoming
 
 ## Uses
 
-Social science research, intended for academic use - 3 labels
+Social science research, intended for academic and nonacademic use
 
 ## Bias, Risks, and Limitations
 
-Single annotator coded the data. Painstakingly.
+Social science approaches to annotation, single annotator coded
 
 ### Recommendations
 
@@ -63,7 +65,7 @@ Please contact me at kumar@merit.unu.edu for instructions on further use
 
 ## How to Get Started with the Model
 
-With a bit of patience, I am still working on this model card
+Forthcoming
 
 ## Training Details
 
@@ -79,7 +81,7 @@ Balanced Accuracy: 0.88
 
 ### Results
 
-Come back later for an updated model card
+Forthcoming
 
 ## Citation 
 
@@ -99,4 +101,4 @@ Come back later for an updated model card
 
 **APA:** Kumar, P. (2025). genAMI. Hugging Face. https://doi.org/10.57967/hf/5784
 
-**Paper**: Forthcoming, in my PhD Thesis 
+**Paper**: Forthcoming