Reset history: keep only eval split

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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
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+# Audio files - compressed
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README.md

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+---
+annotations_creators:
+  - expert-generated
+language_creators:
+  - expert-generated
+language:
+  - nb
+  - nn
+license: cc-by-4.0
+multilinguality:
+  - translation
+pretty_name: Nynorsk Norm 200eval
+size_categories:
+  - 1K<n<10K
+source_datasets:
+  - original
+task_categories:
+  - translation
+task_ids:
+  - text2text-generation
+---
+
+# Nynorsk Norm 200eval
+
+`nynorsk_norm_200eval` is a high-quality, small-scale parallel corpus comprising 200 Norwegian Bokmål–Nynorsk sentence pairs collected from official sources and public institutions. Each example includes:
+
+- `nb`: Original sentence in Bokmål  
+- `nn_original`: Original Nynorsk sentence (typically an official translation)  
+- `nn_husnorm`: Sentence rewritten in Nynorsk following an internal *husnorm* (house style)  
+- `nb_source`, `nn_source`: Source URLs for the Bokmål and Nynorsk versions
+
+## Benchmark
+
+### Target: `nn_original` (official Nynorsk)
+
+| Model            | BLEU | chrF | Notes               |
+|------------------|------|------|---------------------|
+| ExampleModel-v1  | XX.X | XX.X | Official translation baseline |
+| ExampleModel-v2  | XX.X | XX.X | Fine-tuned on government data |
+
+### Target: `nn_husnorm` (house style Nynorsk)
+
+| Model            | BLEU | chrF | Notes                     |
+|------------------|------|------|---------------------------|
+| ExampleModel-v1  | XX.X | XX.X | Without style normalization |
+| ExampleModel-v2  | XX.X | XX.X | Fine-tuned on husnorm corpus |
+
+> Will be replaced with real numbers as soon as we have performed the tests.
+
+
+## Intended Uses
+
+This dataset is intended for:
+
+- Evaluation of Bokmål-to-Nynorsk translation systems  
+- Research on Nynorsk stylistic variation  
+- Style transfer and normalization experiments, especially in public communication
+
+## Format
+
+The dataset is provided as a UTF-8 encoded JSON Lines (`.jsonl`) file. Each line is a structured example:
+```json
+{
+  "nb": "Ledelsen ved NMBU disponerer i dag to elbiler som de kan bruke på møter i nærområdet.",
+  "nn_original": "Leiinga ved NMBU disponerer i dag to elbilar som dei kan bruka på møte i nærområdet.",
+  "nn_husnorm": "Leiinga ved NMBU disponerer i dag to elbilar som dei kan bruke på møte i nærområdet.",
+  "nb_source": "https://www.nmbu.no/om/miljoarbeidet/milj-rsrapport-2020",
+  "nn_source": "https://www.nmbu.no/om/miljoarbeidet/miljotiltak"
+}
+```
+
+## Nynorsk house style ("husnorm")
+
+The `nn_husnorm` field contains Nynorsk text rewritten according to an internal style guide.
+This house norm favors Bokmål-near variants for improved consistency and accessibility in public texts.
+
+General characteristics:
+- Use of samsvarsbøying (agreement)
+- Prefer active voice where natural
+- Rewrite s-genitive using prepositions, compounds, or possessives (sin/si)
+- Use e-infinitive: å komme (not å kome)
+- Use bli, blei, blitt (not verte, vart, vorte)
+- Pronouns: vi, ho, henne (not me, ho, henne)
+- Adverbs: nå, da, derfor, fordi (not no, då, difor, av di)
+- Noun plural forms:
+  - gjestar, nadar instead of gjester, nader
+  - elver, helger instead of elvar, helgar
+- Bokmål-like variants of verbs and nouns:
+  - følge, givar, følgar over følgje, gjevar, følgjar
+- Prefer forelesing, foreslå over førelesing, føreslå
+- Use doubled consonants: komme, lønne (not kome, løne)
+- Lexical choices like nødvendig, allmente are accepted
+
+## Authors
+
+- Husnorm adaptation and linguistic quality control: **Arne Martinus Lidstad** and **Marie Røsok**  
+- Dataset formatting and Hugging Face integration: **Per Egil Kummervold**

extra/prepare_jsonl.py

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+#!/usr/bin/env python3
+import pandas as pd
+import json
+import argparse
+
+def convert_csv_to_jsonl(input_file, output_file):
+    # Read with semicolon delimiter
+    df = pd.read_csv(input_file, delimiter=";", encoding="utf-8")
+    
+    # Drop empty/unnamed columns
+    df = df.drop(columns=[col for col in df.columns if "Unnamed" in col or col.strip() == ""], errors="ignore")
+
+    # Strip leading/trailing spaces from column names
+    df.columns = df.columns.str.strip()
+
+    # Rename to desired schema
+    df = df.rename(columns={
+        "nob": "nb",
+        "nno": "nn_original",
+        "nb_nno": "nn_husnorm",
+        "nob_url": "nb_source",
+        "nno_url": "nn_source"
+    })
+
+    # Validate required fields
+    required = ["nb", "nn_original", "nn_husnorm"]
+    missing = [col for col in required if col not in df.columns]
+    if missing:
+        raise ValueError(f"Missing required columns: {missing}")
+
+    # Write JSONL output
+    with open(output_file, "w", encoding="utf-8") as out_file:
+        for row in df.to_dict(orient="records"):
+            json.dump(row, out_file, ensure_ascii=False)
+            out_file.write("\n")
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Convert CSV to JSONL for nynorsk_norm_200eval")
+    parser.add_argument("--input_file", required=True, help="Path to input CSV file")
+    parser.add_argument("--output_file", required=True, help="Path to output JSONL file")
+    args = parser.parse_args()
+
+    convert_csv_to_jsonl(args.input_file, args.output_file)