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Browse files- src/about.py +3 -0
src/about.py
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@@ -92,6 +92,9 @@ TITLE = """<h1 align="center" id="space-title">🚀 EVALITA-LLM Leaderboard 🚀
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# What does your leaderboard evaluate?
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INTRODUCTION_TEXT = """
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Evalita-LLM, a new benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. The distinguishing and innovative features of Evalita-LLM are the following: (i) **all tasks are native Italian**, avoiding issues of translating from Italian and potential cultural biases; (ii) in addition to well-established **multiple-choice** tasks (6 tasks), the benchmark includes **generative** tasks (4 tasks), enabling more natural interaction with LLMs; (iii) **all tasks are evaluated against multiple prompts**, this way mitigating the model sensitivity to specific prompts and allowing a fairer and objective evaluation.
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"""
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# Which evaluations are you running? how can people reproduce what you have?
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# What does your leaderboard evaluate?
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INTRODUCTION_TEXT = """
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Evalita-LLM, a new benchmark designed to evaluate Large Language Models (LLMs) on Italian tasks. The distinguishing and innovative features of Evalita-LLM are the following: (i) **all tasks are native Italian**, avoiding issues of translating from Italian and potential cultural biases; (ii) in addition to well-established **multiple-choice** tasks (6 tasks), the benchmark includes **generative** tasks (4 tasks), enabling more natural interaction with LLMs; (iii) **all tasks are evaluated against multiple prompts**, this way mitigating the model sensitivity to specific prompts and allowing a fairer and objective evaluation.
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**Multiple Choice**: 📊TE (Textual Entailment), 😃SA (Sentiment Analysis), ⚠️HS (Hate Speech Detection), 🏥AT (Admission Test), 🔤WIC (Word in Context), ❓FAQ (Frequently Asked Questions)
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**Generative**: 🔄LS (Lexical Substitution), 📝SU (Summarization), 🏷️NER (Named Entity Recognition), 🔗REL (Relation Extraction)
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"""
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# Which evaluations are you running? how can people reproduce what you have?
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