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---
language: it
datasets:
- xtreme
---
# Italian-Bert (Italian Bert) + POS πŸŽƒπŸ·
This model is a fine-tuned on [xtreme udpos Italian](https://huggingface.co/nlp/viewer/?dataset=xtreme&config=udpos.Italian) version of [Bert Base Italian](https://huggingface.co/dbmdz/bert-base-italian-cased) for **POS** downstream task.
## Details of the downstream task (POS) - Dataset
- [Dataset: xtreme udpos Italian](https://huggingface.co/nlp/viewer/?dataset=xtreme&config=udpos.Italian) πŸ“š
| Dataset | # Examples |
| ---------------------- | ----- |
| Train | 716 K |
| Dev | 85 K |
- [Fine-tune on NER script provided by @stefan-it](https://raw.githubusercontent.com/stefan-it/fine-tuned-berts-seq/master/scripts/preprocess.py)
- Labels covered:
```
ADJ
ADP
ADV
AUX
CCONJ
DET
INTJ
NOUN
NUM
PART
PRON
PROPN
PUNCT
SCONJ
SYM
VERB
X
```
## Metrics on evaluation set 🧾
| Metric | # score |
| :------------------------------------------------------------------------------------: | :-------: |
| F1 | **97.25**
| Precision | **97.15** |
| Recall | **97.36** |
## Model in action πŸ”¨
Example of usage
```python
from transformers import pipeline
nlp_pos = pipeline(
"ner",
model="sachaarbonel/bert-italian-cased-finetuned-pos",
tokenizer=(
'sachaarbonel/bert-spanish-cased-finetuned-pos',
{"use_fast": False}
))
text = 'Roma Γ¨ la Capitale d'Italia.'
nlp_pos(text)
'''
Output:
--------
[{'entity': 'PROPN', 'index': 1, 'score': 0.9995346665382385, 'word': 'roma'},
{'entity': 'AUX', 'index': 2, 'score': 0.9966597557067871, 'word': 'e'},
{'entity': 'DET', 'index': 3, 'score': 0.9994786977767944, 'word': 'la'},
{'entity': 'NOUN',
'index': 4,
'score': 0.9995198249816895,
'word': 'capitale'},
{'entity': 'ADP', 'index': 5, 'score': 0.9990894198417664, 'word': 'd'},
{'entity': 'PART', 'index': 6, 'score': 0.57159024477005, 'word': "'"},
{'entity': 'PROPN',
'index': 7,
'score': 0.9994804263114929,
'word': 'italia'},
{'entity': 'PUNCT', 'index': 8, 'score': 0.9772886633872986, 'word': '.'}]
'''
```
Yeah! Not too bad πŸŽ‰
> Created by [Sacha Arbonel/@sachaarbonel](https://twitter.com/sachaarbonel) | [LinkedIn](https://www.linkedin.com/in/sacha-arbonel)
> Made with <span style="color: #e25555;">&hearts;</span> in Paris