pytorch t5 text2text-generation es qu transformers quechua translation spanish license:apache-2.0 autotrain_compatible
---
language:
- es
- qu

tags:
- quechua
- translation
- spanish

license: apache-2.0

metrics:
- bleu
- sacrebleu

widget:
- text: "Dios ama a los hombres"
- text: "A pesar de todo, soy feliz"
- text: "¿Qué harán allí?"
- text: "Debes aprender a respetar"

---

# Spanish to Quechua translator

This model is a finetuned version of the [t5-small](https://huggingface.co/t5-small).

## Model description

t5-small-finetuned-spanish-to-quechua has trained for 46 epochs with 102 747 sentences, the validation was performed with 12 844 sentences and 12 843 sentences were used for the test.

## Intended uses & limitations

A large part of the dataset has been extracted from biblical texts, which makes the model perform better with certain types of sentences.

### How to use

You can import this model as follows:

```python
>>> from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
>>> model_name = 'hackathon-pln-es/t5-small-finetuned-spanish-to-quechua'
>>> model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
>>> tokenizer = AutoTokenizer.from_pretrained(model_name)
```

To translate you can do:

```python
>>> sentence = "Entonces dijo"
>>> input = tokenizer(sentence, return_tensors="pt")
>>> output = model.generate(input["input_ids"], max_length=40, num_beams=4, early_stopping=True)
>>> print('Original Sentence: {} \nTranslated sentence: {}'.format(sentence, tokenizer.decode(output[0])))
```

### Limitations and bias

Actually this model only can translate to Quechua of Ayacucho.

## Training data

For train this model we use [Spanish to Quechua dataset](https://huggingface.co/datasets/hackathon-pln-es/spanish-to-quechua)

## Evaluation results

We obtained the following metrics during the training process:

- eval_bleu = 2.9691
- eval_loss = 1.2064628601074219

## Team members

- [Sara Benel](https://huggingface.co/sbenel)
- [Jose Vílchez](https://huggingface.co/JCarlos)
