Update README.md

README.md

@@ -27,20 +27,59 @@ configs:
     path: data/test-*
 ---
 
-Assessing DIScourse COherence in Italian TEXts (DISCOTEX)
+# Assessing DIScourse COherence in Italian TEXts (DISCOTEX)
+
 Original Paper: https://sites.google.com/view/discotex/
 
 Task presented at EVALITA-2023
 
 The original task is about modelling discourse coherence for Italian texts.
 
-We focalized only on the first sub-task: Last sentence Classification: given a short paragraph, and an individual sentence (target), the model will be asked to classify whether the target follows or not the paragraph.
+We focalized only on the first sub-task: **Last Sentence Classification**: given a short paragraph, and an individual sentence (target), the model will be asked to classify whether the target follows or not the paragraph.
 
-To assess the capability of a Language Model to solve such kind of task we reframed the task as multi-choice QA.
+To assess the capability of a Language Model to solve such kind of task we reframed the task as **Multi-Choice QA**.
 
 The question will ask to the model given a short paragraph which target sentence is the correct between a list of four, the answers will be the starting letters of the relative target, and a fifth option that indicate that no one target is the correct continuation.
 
+## Distractors Generation
+
 For each sample, if the sample has 1 as label, we set the relative target as gold answer and three other random targets (from other samples) as distractors. On the other way around, if the sample has 0 as label, we set the relative target and other three random targets (from other samples) as distractors, as the gold answer will be chosen the sentence: "nessuna delle precedenti".
 
-Data statistics:
-- add
+## Example
+
+Here you can see the structure of the single sample in the present dataset.
+
+
+```json
+{
+  "text": string, # text of the short paragraph
+  "choices": list, # list of possible answers, with the correct one plus 4 distractors
+  "label": int, # index of the correct anser in the choices
+}
+```
+
+
+## Statistics 
+
+Training: 16000
+Test: 1600
+
+## 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: "Ti verranno poste delle domande, nelle quali è presente un paragrafo, e come possibili risposte varie frasi che possono essere o meno il continuo.\nIndica la frase che rappresenta la continuazione del paragrafo oppure 'nessuna delle precedenti', se nessuna delle continuazioni è corretta."
+
+Prompt: "Paragrafo: '{{text}}'\nDomanda: Quali delle seguenti frasi presenta una continuazione del precedente paragrafo?\nA. '{{choices[0]}}'\nB. '{{choices[1]}}'\nC. '{{choices[2]}}'\nD. '{{choices[3]}}'\nE. {{choices[4]}}\nRisposta:"
+
+## Some Results
+
+| DISCOTEX | ACCURACY |
+| :--------: | :----: |
+| Mistral-7B | 0 |
+| ZEFIRO | 0 |
+| Llama-3 | 0 |
+| ANITA | 0 |