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---
language:
- en
- es
- eu
datasets:
- squad
---
# Description
This is a basic implementation of the multilingual model ["ixambert-base-cased"](https://huggingface.co/ixa-ehu/ixambert-base-cased), fine-tuned on SQuAD version 1.1, that is able to answer basic factual questions in English, Spanish and Basque.
### Outputs
The model predicts a span of text from the context and a score for the probability for that span to be the correct answer.
### How to use
The model can be used directly with a *question-answering* pipeline:
```python
>>> from transformers import pipeline
>>> context = "Florence Nightingale, known for being the founder of modern nursing, was born in Florence, Italy, in 1820"
>>> question = "When was Florence Nightingale born?"
>>> qa = pipeline("question-answering", model="MarcBrun/ixambert-finetuned-squad")
>>> qa(question=question,context=context)
{'score': 0.9667195081710815, 'start': 101, 'end': 105, 'answer': '1820'}
```
### Hyperparameters
```
batch_size = 8
n_epochs = 3
base_LM_model = "ixambert-base-cased"
learning_rate = 2e-5
lr_schedule = "linear"
max_seq_len = 384
doc_stride = 128
``` |