|
--- |
|
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 |
|
``` |
