---
license: apache-2.0
language: Spanish Nahuatl 
tags:
- translation Spanish Nahuatl 
---

# t5-small-spanish-nahuatl
## Model description
This model is a T5 Transformer ([t5-small](https://huggingface.co/t5-small)) fine-tuned on 29,007 spanish and nahuatl sentences using 12890 samples collected from the web and 16117 samples from the Axolotl dataset.


## Usage
```python
from transformers import AutoModelForSeq2SeqLM
from transformers import AutoTokenizer

model = AutoModelForSeq2SeqLM.from_pretrained('hackathon-pln-es/t5-small-spanish-nahuatl')
tokenizer = AutoTokenizer.from_pretrained('hackathon-pln-es/t5-small-spanish-nahuatl')

model.eval()
sentence = 'muchas flores son blancas'
input_ids = tokenizer('translate Spanish to Nahuatl: ' + sentence, return_tensors='pt').input_ids
outputs = model.generate(input_ids)
# outputs = miak xochitl istak
outputs = tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
```


## Evaluation results
The model is evaluated on 400 validation sentences. 
- Validation loss: 1.56 
- BLEU: 0.13

_Note: Since the Axolotl corpus contains multiple misalignments, the real BLEU and Validation loss are slightly better._


## References
- Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu. 2019. Exploring the limits
of transfer learning with a unified Text-to-Text transformer.

- Gutierrez-Vasques, X., Sierra, G., & Pompa, I. H. (2016). Axolotl: a Web Accessible Parallel Corpus for Spanish-Nahuatl. In LREC.


> Created by [Emilio Morales](https://huggingface.co/milmor).