readme: ---
  language: es
  thumbnail:
  ---
  
  # RuPERTa-base  (Spanish RoBERTa) + NER 🎃🏷
  
  This model is a fine-tuned on [NER-C](https://www.kaggle.com/nltkdata/conll-corpora) version of [RuPERTa-base](https://huggingface.co/mrm8488/RuPERTa-base) for **NER** downstream task.
  
  ## Details of the downstream task (NER) - Dataset
  
  - [Dataset:  CONLL Corpora ES](https://www.kaggle.com/nltkdata/conll-corpora) 📚
  
  | Dataset                | # Examples |
  | ---------------------- | ----- |
  | Train                  |  329 K |
  | Dev                    | 40 K |
  
  
  - [Fine-tune on NER script provided by Huggingface](https://github.com/huggingface/transformers/blob/master/examples/token-classification/run_ner_old.py)
  
  - Labels covered:
  
  ```
  B-LOC
  B-MISC
  B-ORG
  B-PER
  I-LOC
  I-MISC
  I-ORG
  I-PER
  O
  ```
  
  ## Metrics on evaluation set 🧾
  
  |                                                      Metric                                                       |  # score  |
  | :------------------------------------------------------------------------------------: | :-------: |
  | F1                                       | **77.55**  
  | Precision                                | **75.53** | 
  | Recall                                   | **79.68** |    
  
  ## Model in action 🔨
  
  
  Example of usage:
  
  ```python
  import torch
  from transformers import AutoModelForTokenClassification, AutoTokenizer
  
  id2label = {
      "0": "B-LOC",
      "1": "B-MISC",
      "2": "B-ORG",
      "3": "B-PER",
      "4": "I-LOC",
      "5": "I-MISC",
      "6": "I-ORG",
      "7": "I-PER",
      "8": "O"
  }
  
  text ="Julien, CEO de HF, nació en Francia."
  input_ids = torch.tensor(tokenizer.encode(text)).unsqueeze(0)
  
  outputs = model(input_ids)
  last_hidden_states = outputs[0]
  
  for m in last_hidden_states:
    for index, n in enumerate(m):
      if(index > 0 and index <= len(text.split(" "))):
        print(text.split(" ")[index-1] + ": " + id2label[str(torch.argmax(n).item())])
        
  '''
  Output:
  --------
  Julien,: I-PER
  CEO: O
  de: O
  HF,: B-ORG
  nació: I-PER
  en: I-PER
  Francia.: I-LOC
  '''
  ```
  Yeah! Not too bad 🎉
  
  > Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488)
  
  > Made with <span style="color: #e25555;">&hearts;</span> in Spain
  