This model is a fine-tuned on [NER-C](https://www.kaggle.com/nltkdata/conll-corpora) Of the Spanish BERT cased [(BETO)](https://github.com/dccuchile/beto) for **POS** (Part of Speech tagging) downstream task.
## Details of the downstream task (POS) - Dataset
-[Dataset: CONLL Corpora ES](https://www.kaggle.com/nltkdata/conll-corpora) with data augmentation techniques
I preprocessed the dataset and splitted it as train / dev (80/20)
| Dataset | # Examples |
| ---------------------- | ----- |
| Train | 340 K |
| Dev | 50 K |
-[Fine-tune on NER script provided by Huggingface](https://github.com/huggingface/transformers/blob/master/examples/run_ner.py)
- Labels covered:
```
AO, AQ, CC, CS, DA, DD, DE, DI, DN, DP, DT, Faa, Fat, Fc, Fd, Fe, Fg, Fh, Fia, Fit, Fp, Fpa, Fpt, Fs, Ft, Fx, Fz, I, NC, NP, P0, PD, PI, PN, PP, PR, PT, PX, RG, RN, SP, VAI, VAM, VAN, VAP, VAS, VMG, VMI, VMM, VMN, VMP, VMS, VSG, VSI, VSM, VSN, VSP, VSS, Y and Z