---
language: 
- ru
- uk
- be
- kk
- az
- hy
- ka
- he
- en
- de
tags:
- language classification
- text segmentation
datasets:
- open_subtitles
- tatoeba
- oscar
---

# RoBERTa for Multilabel Language Segmentation
## Training
RoBERTa fine-tuned on small parts of Open Subtitles, Oscar and Tatoeba datasets (~9k samples per language).

Implemented heuristic algorithm for multilingual training data creation with generation of target masks- https://github.com/n1kstep/lang-classifier

| data source          | language          |
|-----------------|----------------|
| open_subtitles    | ka, he, en, de |
| oscar      | be, kk, az, hu |
| tatoeba     | ru, uk         |

## Validation
The metrics obtained from validation on the another part of dataset (~1k samples per language).

| Validation Loss | Precision | Recall   | F1-Score | Accuracy |
|-----------------|-----------|----------|----------|----------|
| 0.029172        | 0.919623  | 0.933586 | 0.926552 | 0.991883 |