opus-mt-ca-pt
| Property | Value |
|---|---|
| License | Apache 2.0 |
| Architecture | Transformer-align |
| BLEU Score | 44.9 |
| chrF Score | 0.658 |
What is opus-mt-ca-pt?
opus-mt-ca-pt is a specialized neural machine translation model developed by Helsinki-NLP for translating text from Catalan to Portuguese. Built using the transformer-align architecture, this model demonstrates impressive performance with a BLEU score of 44.9 and a chrF score of 0.658 on the Tatoeba test set.
Implementation Details
The model employs normalization and SentencePiece tokenization with spm12k vocabulary for both source and target languages. It was trained on June 17, 2020, and is part of the broader OPUS machine translation initiative.
- Pre-processing: Normalization + SentencePiece (spm12k,spm12k)
- Source Language: Catalan (ca)
- Target Language: Portuguese (pt)
- Training Framework: Marian-NMT
Core Capabilities
- High-quality translation from Catalan to Portuguese
- Optimized for production deployment
- Supports inference endpoints
- Compatible with both PyTorch and TensorFlow frameworks
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in Catalan to Portuguese translation with state-of-the-art performance metrics, demonstrated by its high BLEU score of 44.9. It uses advanced tokenization techniques and is specifically optimized for this language pair.
Q: What are the recommended use cases?
The model is ideal for applications requiring high-quality translation between Catalan and Portuguese, such as content localization, document translation, and cross-lingual information retrieval systems.
