| # ÈwéBench — Scoring Methodology |
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| [English](#english) • [Français](#français) |
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| ## English |
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| ### Overview |
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| ÈwéBench uses a **weighted multi-category scoring** system. Each model receives a single **ÈwéScore** (0-100) that represents its overall capability in Ewe. |
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| ### Formula |
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| ``` |
| ÈwéScore = Σ (category_score × category_weight) / Σ active_weights |
| ``` |
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| Where: |
| - `category_score` = average test score within a category (0-100) |
| - `category_weight` = importance weight of that category |
| - `active_weights` = sum of weights for categories that were actually evaluated (handles partial runs) |
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| ### Weight Rationale |
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| | Category | Weight | Justification | |
| |----------|--------|---------------| |
| | Linguistic Comprehension | 15% | Core: understanding Ewe grammar, tones, morphology | |
| | Text Generation | 15% | Core: producing natural, fluent Ewe text | |
| | Reasoning | 12% | Important: expressing logical thought in Ewe | |
| | Translation | 12% | Important: practical bilingual capability | |
| | Cultural Knowledge | 10% | Valuable: proverbs, traditions, history | |
| | Instruction Following | 10% | Practical: real-world usability | |
| | Multi-turn | 8% | Advanced: conversation coherence | |
| | Agentic | 8% | Advanced: tool use and planning | |
| | Style Adaptation | 5% | Bonus: register switching | |
| | Robustness | 5% | Bonus: adversarial resilience | |
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| Weights sum to **100%**. Categories are ordered by importance: language mastery first, then practical capabilities, then advanced features. |
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| ### Test Scoring |
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| Each individual test is scored **0.0 to 1.0** using one of these methods: |
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| #### 1. Exact Match (`exact_match`) |
| ```python |
| score = 1.0 if normalize(expected) == normalize(response) else 0.0 |
| ``` |
| Used for factual questions with a single correct answer. |
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| #### 2. Keyword Presence (`keywords`) |
| ```python |
| score = count(found_keywords) / count(expected_keywords) |
| ``` |
| Used for open-ended questions where specific Ewe terms should appear. |
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| #### 3. Multiple Choice (`multiple_choice`) |
| ```python |
| score = 1.0 if correct_letter detected in response else 0.0 |
| ``` |
| Used for QCM-style tests with A/B/C/D options. |
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| #### 4. Format Compliance (`format`) |
| Checks multiple format criteria: |
| - `contains_ewe` — Response has Ewe characters (ɖ, ɛ, ɔ, ƒ, ŋ, ɣ) |
| - `min_length` / `max_length` — Response length bounds |
| - `contains_function_call` — Has `<function_call>` tag |
| - `markdown_elements` — Has tables, headers, lists, bold |
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| #### 5. Ewe Quality Heuristic (`ewe_quality`) |
| Composite heuristic scoring: |
| - +0.3 for Ewe special characters presence |
| - +0.05 per common Ewe word found (max +0.4) |
| - -0.2 if too many French words detected (>5) |
| - +0.2 for multi-sentence structure |
| - +0.1 for minimum response length |
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| #### 6. Composite (`composite`) |
| ```python |
| score = (keywords_score + ewe_quality_score + format_score) / 3 |
| ``` |
| Used for complex tests requiring multiple evaluation dimensions. |
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| ### Pass/Fail Threshold |
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| A test is **passed** if `score >= 0.7`. |
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| This threshold balances: |
| - Not too strict (some Ewe variability is expected) |
| - Not too lenient (ensures meaningful output quality) |
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| ### Category Score |
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| ``` |
| category_score = (sum of test scores / number of tests) × 100 |
| ``` |
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| --- |
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| ## Français |
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| ### Vue d'ensemble |
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| ÈwéBench utilise un système de **scoring multi-catégories pondéré**. Chaque modèle reçoit un **ÈwéScore** unique (0-100) représentant sa capacité globale en Ewe. |
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| ### Formule |
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| ``` |
| ÈwéScore = Σ (score_catégorie × poids_catégorie) / Σ poids_actifs |
| ``` |
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| ### Justification des poids |
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| | Catégorie | Poids | Justification | |
| |-----------|-------|---------------| |
| | Compréhension Linguistique | 15% | Cœur : compréhension grammaire, tons, morphologie Ewe | |
| | Génération de Texte | 15% | Cœur : production de texte Ewe naturel et fluide | |
| | Raisonnement | 12% | Important : expression de la pensée logique en Ewe | |
| | Traduction | 12% | Important : capacité bilingue pratique | |
| | Connaissance Culturelle | 10% | Précieux : proverbes, traditions, histoire | |
| | Suivi d'Instructions | 10% | Pratique : utilisabilité réelle | |
| | Multi-tour | 8% | Avancé : cohérence conversationnelle | |
| | Agentique | 8% | Avancé : utilisation d'outils et planification | |
| | Adaptation Stylistique | 5% | Bonus : changement de registre | |
| | Robustesse | 5% | Bonus : résilience adversariale | |
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| ### Seuil de réussite |
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| Un test est **réussi** si `score >= 0.7`. |
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| ### Score par catégorie |
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| ``` |
| score_catégorie = (somme des scores de tests / nombre de tests) × 100 |
| ``` |
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| --- |
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| ## Known Limitations |
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| 1. **Ewe quality heuristic** is rule-based, not learned — it can miss valid Ewe or reward superficial patterns |
| 2. **Keyword matching** doesn't account for synonyms or paraphrasing |
| 3. **No human evaluation** in automated runs — ÈwéScore is an approximation |
| 4. **Tonal accuracy** cannot be verified in written text (Ewe is tonal but rarely written with tone marks) |
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| These limitations are documented so users interpret scores with appropriate context. We plan to add human evaluation protocols in v2.0. |
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