--- language: it datasets: - xtreme --- # Italian-Bert (Italian Bert) + POS ๐ŸŽƒ๐Ÿท 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) ๐Ÿ“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 ๐Ÿงพ | Metric | # score | | :------------------------------------------------------------------------------------: | :-------: | | F1 | **97.25** | Precision | **97.15** | | Recall | **97.36** | ## Model in action ๐Ÿ”จ 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 รจ 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 ๐ŸŽ‰ > Created by [Sacha Arbonel/@sachaarbonel](https://twitter.com/sachaarbonel) | [LinkedIn](https://www.linkedin.com/in/sacha-arbonel) > Made with in Paris