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---
base_model: bert-base-multilingual-uncased
model-index:
- name: lang-recogn-model
results:
- task:
type: text-classification
dataset:
name: language-detection
type: language-detection
metrics:
- name: accuracy
type: accuracy
value: 0.9836
source:
name: Language recognition using BERT
url: >-
https://www.kaggle.com/code/sergeypolivin/language-recognition-using-bert
language:
- ar
- da
- nl
- en
- fr
- de
- el
- hi
- it
- kn
- ml
- pt
- ru
- es
- sv
- ta
- tr
pipeline_tag: text-classification
widget:
- text: "Hello, world"
example_title: "English language"
- text: "Ik heb het al gezien"
example_title: "Dutch language"
---
# Language Detection Model
The model presented in the following repository represents a fine-tuned version of `BertForSequenceClassification`
pretrained on [multilingual texts](https://huggingface.co/bert-base-multilingual-uncased).
## Training/fine-tuning
The model has been fine-tuned based on [Language Detection](https://www.kaggle.com/datasets/basilb2s/language-detection)
dataset found on *Kaggle*. The entire process of the dataset analysis as well as a complete description of the training procedure
can be found in [one of my *Kaggle* notebooks](https://www.kaggle.com/code/sergeypolivin/language-recognition-using-bert)
which has been used for the purpose of a faster model training on *GPU*.
## Supported languages
The model has been fine-tuned to detect one of the following 17 languages:
- Arabic
- Danish
- Dutch
- English
- French
- German
- Greek
- Hindi
- Italian
- Kannada
- Malayalam
- Portugeese
- Russian
- Spanish
- Sweedish
- Tamil
- Turkish
## References
1. [BERT multilingual base model (uncased)](https://huggingface.co/bert-base-multilingual-uncased)
2. [Language Detection Dataset](https://www.kaggle.com/datasets/basilb2s/language-detection)