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xlm-roberta-large-ner-kazakh

Token Classification
Transformers
PyTorch
Safetensors
Kazakh
xlm-roberta
Named Entity Recognition
NER
Inference Endpoints
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  # A Named Entity Recognition Model for Kazakh
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  - The model was inspired by the [LREC 2022](https://lrec2022.lrec-conf.org/en/) paper [*KazNERD: Kazakh Named Entity Recognition Dataset*](https://aclanthology.org/2022.lrec-1.44).
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  - The original repository for the paper can be found at *https://github.com/IS2AI/KazNERD*.
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- ## Differences
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  While the original dataset contained tokens denoting speech disfluencies and hesitations (parenthesised) and background noise [bracketed], this model was trained on a version of the dataset where such tokens and duplicates were removed.
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- As a result, the number of sentences, tokens, and named entities (NEs) in the cleaned dataset changed. It is also likely that token numbers were calculated incorrectly in the original dataset and should have been given as 1,120,387 (Train), 136,983 (Valid), 134,540 (Test), and 1,391,910 (Total).
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- Dataset | Unit | Train | Valid | Test | Total |
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- | :---: | :---: | :---: | :---: | :---: | :---: |
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- KazNERD (Original)| Sentence | 90,228 (80.06%) | 11,167 (9.91%)| 11,307 (10.03%) | 112,702 (100%) |
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- KazNERD (Cleaned) | Sentence | 88,540 (80.00%) | 11,067 (10.00%) | 11,068 (10.00%) | 110,675 (100%) |
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- KazNERD (Original)| Token | 1,043,305 (80.11%) | 129,223 (9.92%)| 129,824 (9.97%) | 1,302,352 (100%) |
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- KazNERD (Cleaned) | Token | 1,088,461 (80.04%) | 136,021 (10.00%) | 135,426 (9.96%) | 1,359,908 (100%) |
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- KazNERD (Original)| NE | 109,342 (80.20%) | 13,483 (9.89%)| 13,508 (9.91%) | 136,333 (100%) |
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- KazNERD (Cleaned) | NE | 106,148 (80.17%) | 13,189 (9.96%) | 13,072 (9.87%) | 132,409 (100%) |
 
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  # A Named Entity Recognition Model for Kazakh
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  - The model was inspired by the [LREC 2022](https://lrec2022.lrec-conf.org/en/) paper [*KazNERD: Kazakh Named Entity Recognition Dataset*](https://aclanthology.org/2022.lrec-1.44).
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  - The original repository for the paper can be found at *https://github.com/IS2AI/KazNERD*.
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+ ## KazNERD (cleaned)
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  While the original dataset contained tokens denoting speech disfluencies and hesitations (parenthesised) and background noise [bracketed], this model was trained on a version of the dataset where such tokens and duplicates were removed.
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+ As a result, the number of sentences, tokens, and named entities (NEs) in the cleaned dataset changed.
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+ | Unit | Train | Valid | Test | Total |
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+ | :---: | :---: | :---: | :---: | :---: |
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+ | Sentence | 88,540 (80.00%) | 11,067 (10.00%) | 11,068 (10.00%) | 110,675 (100%) |
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+ | Token | 1,088,461 (80.04%) | 136,021 (10.00%) | 135,426 (9.96%) | 1,359,908 (100%) |
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+ | NE | 106,148 (80.17%) | 13,189 (9.96%) | 13,072 (9.87%) | 132,409 (100%) |