---
language: 
- ru
- uk
- be
- kk
- az
- hy
- ka
- he
- en
- de
tags:
- language
- classification
datasets:
- Open Subtitles
- Tatoeba
- Oscar
---

Model for Single Language Classification in texts. Supports 10 languages: ru, uk, be, kk, az, hy, ka, he, en, de.

Model trained on small parts of Open Subtitles, Oscar and Tatoeba datasets (~9k samples per language).

The metrics obtained from validation part of dataset (~1k samples per language).

| eval_accuracy | eval_az_f1-score | eval_az_precision | eval_az_recall | eval_az_support | eval_be_f1-score   | eval_be_precision | eval_be_recall     | eval_be_support | eval_de_f1-score   | eval_de_precision | eval_de_recall     | eval_de_support | eval_en_f1-score   | eval_en_precision | eval_en_recall     | eval_en_support | eval_he_f1-score   | eval_he_precision | eval_he_recall    | eval_he_support | eval_hy_f1-score   | eval_hy_precision | eval_hy_recall     | eval_hy_support | eval_ka_f1-score | eval_ka_precision | eval_ka_recall | eval_ka_support | eval_kk_f1-score   | eval_kk_precision | eval_kk_recall     | eval_kk_support | eval_loss           | eval_macro avg_f1-score | eval_macro avg_precision | eval_macro avg_recall | eval_macro avg_support | eval_ru_f1-score   | eval_ru_precision | eval_ru_recall     | eval_ru_support | eval_uk_f1-score   | eval_uk_precision | eval_uk_recall     | eval_uk_support | eval_weighted avg_f1-score | eval_weighted avg_precision | eval_weighted avg_recall | eval_weighted avg_support |
| ------------- | ---------------- | ----------------- | -------------- | --------------- | ------------------ | ----------------- | ------------------ | --------------- | ------------------ | ----------------- | ------------------ | --------------- | ------------------ | ----------------- | ------------------ | --------------- | ------------------ | ----------------- | ----------------- | --------------- | ------------------ | ----------------- | ------------------ | --------------- | ---------------- | ----------------- | -------------- | --------------- | ------------------ | ----------------- | ------------------ | --------------- | ------------------- | ----------------------- | ------------------------ | --------------------- | ---------------------- | ------------------ | ----------------- | ------------------ | --------------- | ------------------ | ----------------- | ------------------ | --------------- | -------------------------- | --------------------------- | ------------------------ | ------------------------- |
| 0.99          | 0.99849774661993 | 0.997             | 1              | 997             | 0.9960079840319361 | 0.998             | 0.9940239043824701 | 1004            | 0.9762506316321374 | 0.966             | 0.9867211440245148 | 979             | 0.9762376237623762 | 0.986             | 0.9666666666666667 | 1020            | 0.9995002498750626 | 1                 | 0.999000999000999 | 1001            | 0.9944806823883593 | 0.991             | 0.9979859013091642 | 993             | 0.999            | 0.999             | 0.999          | 1000            | 0.9955112219451371 | 0.998             | 0.9930348258706467 | 1005            | 0.04831727221608162 | 0.9899994666596248      | 0.99                     | 0.9901305007950791    | 10000                  | 0.9822425164890917 | 0.968             | 0.9969104016477858 | 971             | 0.9822660098522168 | 0.997             | 0.9679611650485437 | 1030            | 0.9900005333403753         | 0.9901326000000001          | 0.99                     | 10000                     |