Create model card (#3487)
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language: spanish
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thumbnail:
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---
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# Spanish BERT (BETO) + Syntax POS tagging ✍🏷
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This model is a fine-tuned version of the Spanish BERT [(BETO)](https://github.com/dccuchile/beto) on Spanish **syntax** annotations in [CONLL CORPORA](https://www.kaggle.com/nltkdata/conll-corpora) dataset for **syntax POS** (Part of Speech tagging) downstream task.
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## Details of the downstream task (Syntax POS) - Dataset
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- [Dataset: CONLL Corpora ES](https://www.kaggle.com/nltkdata/conll-corpora)
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#### [Fine-tune script on NER dataset provided by Huggingface](https://github.com/huggingface/transformers/blob/master/examples/run_ner.py)
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#### 21 Syntax annotations (Labels) covered:
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- \_
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- ATR
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- ATR.d
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- CAG
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- CC
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- CD
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- CD.Q
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- CI
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- CPRED
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- CPRED.CD
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- CPRED.SUJ
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- CREG
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- ET
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- IMPERS
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- MOD
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- NEG
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- PASS
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- PUNC
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- ROOT
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- SUJ
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- VOC
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## Metrics on test set 📋
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| Metric | # score |
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| :-------: | :-------: |
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| F1 | **89.27** |
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| Precision | **89.44** |
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| Recall | **89.11** |
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## Model in action 🔨
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Fast usage with **pipelines** 🧪
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```python
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from transformers import pipeline
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nlp_pos_syntax = pipeline(
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"ner",
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model="mrm8488/bert-spanish-cased-finetuned-pos-syntax",
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tokenizer="mrm8488/bert-spanish-cased-finetuned-pos-syntax"
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)
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text = 'Mis amigos están pensando viajar a Londres este verano.'
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nlp_pos_syntax(text)[1:len(nlp_pos_syntax(text))-1]
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```
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```json
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[
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{ "entity": "_", "score": 0.9999216794967651, "word": "Mis" },
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{ "entity": "SUJ", "score": 0.999882698059082, "word": "amigos" },
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{ "entity": "_", "score": 0.9998869299888611, "word": "están" },
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{ "entity": "ROOT", "score": 0.9980518221855164, "word": "pensando" },
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{ "entity": "_", "score": 0.9998420476913452, "word": "viajar" },
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{ "entity": "CD", "score": 0.999351978302002, "word": "a" },
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{ "entity": "_", "score": 0.999959409236908, "word": "Londres" },
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{ "entity": "_", "score": 0.9998968839645386, "word": "este" },
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{ "entity": "CC", "score": 0.99931401014328, "word": "verano" },
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{ "entity": "PUNC", "score": 0.9998534917831421, "word": "." }
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]
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```
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> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)
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> Made with <span style="color: #e25555;">♥</span> in Spain
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