--- language: spanish thumbnail: https://i.imgur.com/jgBdimh.png --- # Spanish BERT (BETO) + NER 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 **NER** downstream task. ## Details of the downstream task (NER) - Dataset - [Dataset: CONLL Corpora ES](https://www.kaggle.com/nltkdata/conll-corpora) I preprocessed the dataset and splitted it as train / dev (80/20) | Dataset | # Examples | | ---------------------- | ----- | | Train | 8.7 K | | Dev | 2.2 K | - [Fine-tune on NER script](https://github.com/huggingface/transformers/blob/master/examples/run_ner.py) ```bash !export NER_DIR='/content/ner_dataset' !python /content/transformers/examples/run_ner.py \ --model_type bert \ --model_name_or_path dccuchile/bert-base-spanish-wwm-cased \ --do_train \ --do_eval \ --data_dir '/content/ner_dataset' \ --num_train_epochs 15.0 \ --max_seq_length 384 \ --output_dir /content/model_output \ --save_steps 5000 \ ``` ## Comparison: | Model | # score | | :--------------------------------------------------------------------------------------------------------------: | :-------: | | bert-base-spanish-wwm-cased (BETO) | 88.43 | | [bert-spanish-cased-finetuned-ner (this one)](https://huggingface.co/mrm8488/bert-spanish-cased-finetuned-ner) | **89.65** | | Best Multilingual BERT | 87.38 | ``` ***** All metrics on Eval results ***** f1 = 0.8965040489828165 loss = 0.11504213575173258 precision = 0.893679858239811 recall = 0.8993461462254805 ``` > Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488) > Made with in Spain