Update README.md

README.md

@@ -49,7 +49,7 @@ configs:
     path: Synth/test-*
 ---
 
-# Automatic Misogyny Identification (AMI)
+# Automatic Misogyny Identification (AMI)
 
 Original Paper: https://amievalita2020.github.io
 
@@ -59,8 +59,32 @@ This task consists of tweet classification, specifically, categorization of the
 
 We taken both subtasks, *raw_dataset* uploaded as *Behaviour* (3 class classification) and *synthetic* uploaded as *Synth* (2 class classification).
 
-Data statistics:
-- add
+## Statitics
 
-Proposed Prompts:
-- add
+| AMI Behaviour | Non Misogino | Misogino | Misogino Aggressivo |
+| -------- | ------- | ------- |
+| Training | 2663 | 554 | 1783 |
+| Test | 500 | 324 | 176 |
+
+| AMI Synth | Non Misogino | Misogino | 
+| -------- | ------- | 
+| Training | 3670 | 3344 | 
+| Test | 1454 | 1454 | 
+
+
+## Proposed Prompts
+
+Here we will describe the prompt given to the model over which we will compute the perplexity score, as model's answer we will chose the prompt with lower perplexity.
+Moreover, for each subtask, we define a description that is prepended to the prompts, needed by the model to understand the task.
+
+### Behaviour
+
+Description of the task: "Indica il livello di misoginia presente nei seguenti tweets."
+Label (Non Misogino): "Tweet: '{{text}}'.\nIl tweet non presenta alcun elemento misogino"
+Label (Misogino): "Tweet: '{{text}}'.\nIl tweet presenta caratteristiche misogine"
+Label (Misogino Aggressivo): "Tweet: '{{text}}'.\nIl tweet presenta caratteristiche misogine aggressive"
+
+### Synth
+Description of the task: "Indica se i seguenti tweets presentano caratteristiche o elementi misogini."
+Label (Non Misogino): "Tweet: '{{text}}'.\nIl tweet non presenta alcun elemento misogino"
+Label (Misogino): "Tweet: '{{text}}'.\nIl tweet presenta caratteristiche misogine"