From 29ab4b7f4027b79ebc2c0456c1d09410e98df682 Mon Sep 17 00:00:00 2001
From: Manuel Romero <mrm8488@gmail.com>
Date: Mon, 17 Feb 2020 15:23:11 +0100
Subject: [PATCH] Create README.md

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+---
+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 <span style="color: #e25555;">&hearts;</span> in Spain