Update README.md

README.md

@@ -8,7 +8,7 @@ tags:
 - propaganda
 ---
 
-# Model Card for identrics/BG_propaganda_detector
+# Model Card for identrics/wasper_propaganda_detection_bg
 
 
 
@@ -24,12 +24,12 @@ tags:
 ## Model Description
 
 This model consists of a fine-tuned version of BgGPT-7B-Instruct-v0.2 for a propaganda detection task. It is effectively a binary classifier, determining wether propaganda is present in the output string.
-This model was created by [`Identrics`](https://identrics.ai/), in the scope of the WASPer project. The detailed taxonomy could be found [here](https://github.com/Identrics/wasper/).
+This model was created by [`Identrics`](https://identrics.ai/), in the scope of the WASPer project.The detailed taxonomy of the full pipeline could be found [here](https://github.com/Identrics/wasper/).
 
 
 ## Uses
 
-To be used as a binary classifier to identify if propaganda is present in a string containing a comment from a social media site
+Designed as a binary classifier to determine whether a traditional or social media comment contains propaganda.
 
 ### Example
 
@@ -52,14 +52,14 @@ print(output.logits)
 
 
 ## Training Details
+The training dataset for the model consists of a balanced collection of Bulgarian examples, including both propaganda and non-propaganda content. These examples were sourced from a variety of traditional media and social media platforms and manually annotated by domain experts. Additionally, the dataset is enriched with AI-generated samples.
 
-The training datasets for the model consist of a balanced set totaling 734 Bulgarian examples that include both propaganda and non-propaganda content. These examples are collected from a variety of traditional media and social media sources, ensuring a diverse range of content. Aditionally, the training dataset is enriched with AI-generated samples. The total distribution of the training data is shown in the table below: 
+The model achieved an F1 score of 0.836 during evaluation.
 
+## Compute Infrastructure
+This model was fine-tuned using a **GPU / 2xNVIDIA Tesla V100 32GB**.
 
-The model was then tested on a smaller evaluation dataset, achieving an F1 score of 0.836.
-
-
-## Citation
+## Citation [this section is to be updated soon]
 
 If you find our work useful, please consider citing WASPer: