opus-mt-fi-en
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Developer | Helsinki-NLP |
| Architecture | Transformer-align |
| BLEU Score | 53.4 (Tatoeba test) |
What is opus-mt-fi-en?
opus-mt-fi-en is a specialized neural machine translation model developed by Helsinki-NLP for translating Finnish text to English. Built using the transformer-align architecture, this model demonstrates exceptional performance with a BLEU score of 53.4 on the Tatoeba test set and impressive chrF scores across various benchmarks.
Implementation Details
The model employs normalization and SentencePiece preprocessing with spm32k tokenization for both source and target languages. It was trained on August 5, 2020, and has been extensively tested across multiple news test sets, consistently showing strong performance with BLEU scores ranging from 23.8 to 32.3.
- Pre-processing: Normalization + SentencePiece (spm32k,spm32k)
- Source Language: Finnish (fin)
- Target Language: English (eng)
- Training Framework: PyTorch and TensorFlow compatible
Core Capabilities
- High-quality Finnish to English translation
- Robust performance across various news domains
- Excellent handling of Finnish linguistic structures
- Strong performance on both formal and informal text
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its exceptional performance on Finnish to English translation, demonstrated by its high BLEU score of 53.4 on the Tatoeba test set, significantly outperforming many other language pairs.
Q: What are the recommended use cases?
This model is ideal for professional Finnish to English translation tasks, particularly in news translation, document translation, and general content localization. It's especially effective for formal content, as evidenced by its strong performance on news test sets.
