More metadata

README.md

@@ -28,10 +28,119 @@ configs:
     path: doc_type_v2_primary/validation.jsonl.zst
   - split: test
     path: doc_type_v2_primary/test.jsonl.zst
+language_creators:
+- machine-translated
+- curated
+task_categories:
+- text-classification
+tags:
+- cross-lingual-classification
+- domain-adaptation
+- multilingual
+language:
+- afr
+- als
+- amh
+- arb
+- ars
+- ary
+- arz
+- asm
+- azj
+- bel
+- ben
+- bew
+- bos
+- bul
+- cat
+- ces
+- ckb
+- cmn
+- cym
+- dan
+- deu
+- div
+- ekk
+- ell
+- eng
+- epo
+- eus
+- fao
+- fas
+- fil
+- fin
+- fra
+- fry
+- gle
+- glg
+- guj
+- hau
+- heb
+- hin
+- hrv
+- hun
+- hye
+- ind
+- isl
+- ita
+- jpn
+- kan
+- kat
+- kaz
+- khk
+- khm
+- kin
+- kir
+- kmr
+- kor
+- lao
+- lat
+- lit
+- ltz
+- lvs
+- mal
+- mar
+- mkd
+- mlt
+- mya
+- nld
+- nno
+- nob
+- npi
+- nrm
+- ory
+- pan
+- pbt
+- plt
+- pol
+- por
+- ron
+- rus
+- sin
+- slk
+- slv
+- snd
+- som
+- spa
+- srp
+- swe
+- swh
+- tam
+- tel
+- tgk
+- tha
+- tur
+- ukr
+- urd
+- uzn
+- vie
+- xho
+- yue
+- zsm
 ---
 # Multilingual Document Classification Dataset
 
-This dataset contains **100,000 text passages** across **100 non-English languages** sourced from the [`agentlans/HuggingFaceFW-finetranslations-100-languages-sample`]([https://huggingface.co/datasets/agentlans/HuggingFaceFW-finetranslations-100-languages-sample](https://huggingface.co/datasets/agentlans/HuggingFaceFW-finetranslations-100-languages-sample)) collection. 
+This dataset contains **100,000 text passages** across **100 non-English language-script pairs** sourced from the [`agentlans/HuggingFaceFW-finetranslations-100-languages-sample`]([https://huggingface.co/datasets/agentlans/HuggingFaceFW-finetranslations-100-languages-sample](https://huggingface.co/datasets/agentlans/HuggingFaceFW-finetranslations-100-languages-sample)) collection. 
 
 Each original text passage is paired with its English translation and has been programmatically annotated with domain, writing genre, and educational classifications to facilitate cross-lingual classification and domain adaptation tasks.
 
@@ -46,7 +155,7 @@ Each original text passage is paired with its English translation and has been p
 
 The dataset contains subset configurations tailored for specific training objectives. 
 * In the **`main` config**, each original text is stored alongside its English translation within a single row.
-* In **subset configs** (e.g., configurations filtered or categorized by specific schema labels), the original texts and their English translations are stored as distinct, individual rows to allow direct training on the target language or translation.
+* In **subset configs** (for example, configurations filtered or categorized by specific schema labels), the original texts and their English translations are stored as distinct, individual rows to allow direct training on the target language or translation.
 
 ## Annotation & Classification Details
 
@@ -59,7 +168,7 @@ To generate granular metadata for domain, genre, and cognitive level, two primar
 
 | Column Name | Source Model | Description / Purpose |
 | :--- | :--- | :--- |
-| `nvidia_domain` | NVIDIA Domain Classifier | General topical categorization (e.g., News, Food & Drink). |
+| `nvidia_domain` | NVIDIA Domain Classifier | General topical categorization (for example, News, Food & Drink). |
 | `doc_type_v1_primary` | EAI Distill 0.5B | High-level document genre classification (V1). |
 | `doc_type_v2_primary` | EAI Distill 0.5B | Refined, granular document type classification (V2). |
 
@@ -115,9 +224,9 @@ The subset configurations are stripped down to the target `text`, its `language`
 Users should keep the following limitations in mind when utilizing this dataset:
 
 * **Source Translation Quality:** Since the source texts are derived from `HuggingFaceFW-finetranslations`, any artifacts, vocabulary choices, or grammatical inaccuracies in the underlying translations will carry over.
-* **Language Distribution:** The dataset contains an uniform number of samples across languages. As a result, high-resource languages (e.g., Mandarin Chinese) have the same number of rows as lower-resource languages (e.g., Assamese).
+* **Language Distribution:** The dataset contains an uniform number of samples across languages. As a result, high-resource languages (for example, Mandarin Chinese) have the same number of rows as lower-resource languages (for example, Assamese).
 * **Class Imbalance:** Certain topical domains and document types are heavily over-represented compared to others. For instance, there are far more promotional news articles than niche categories like culinary recipes.
 
-## License
+## Licence
 
 This dataset is released under the **Open Data Commons Attribution License (ODC-BY)**, matching the terms of the source datasets.