https://github.com/ManivannanMurugavel/spacy-ner-annotator

Train Spacy ner with custom dataset
https://github.com/ManivannanMurugavel/spacy-ner-annotator

annotator-spacy ner-annotator nlp-annotator spacy-ner spacy-ner-annotator spacy-nlp spacy-nlp-ner

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Train Spacy ner with custom dataset

• Host: GitHub
• URL: https://github.com/ManivannanMurugavel/spacy-ner-annotator
• Owner: ManivannanMurugavel
• Created: 2019-03-27T13:48:08.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2022-11-07T03:08:27.000Z (about 2 years ago)
• Last Synced: 2024-08-03T21:01:13.882Z (4 months ago)
• Topics: annotator-spacy, ner-annotator, nlp-annotator, spacy-ner, spacy-ner-annotator, spacy-nlp, spacy-nlp-ner
• Language: JavaScript
• Homepage: https://medium.com/@manivannan_data/how-to-train-ner-with-custom-training-data-using-spacy-188e0e508c6
• Size: 647 KB
• Stars: 183
• Watchers: 14
• Forks: 112
• Open Issues: 6
• Metadata Files:
  • Readme: README.md

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README

        
# spacy-ner-annotator

## Installation

pip3 install spacy

## Steps for usage

1. Open `index.html` file and open data on it. 

2. Post annotations download the data and convert to spacy format using `convert_spacy_train_data.py`

3. Split data into train and test if you wish and add it to `train.py`

4. finally run the train.py after setting the hyper-parameters. Iterations are losses are logged in `output_log.txt`. And precision, recall and f1 scores are logged in `train_output.txt` and `test_output.txt`

5. Check progress by running `losses_plotter.py`.

6. If you wish to train over a model download the model and add its name in `train.py` 

## Details & Credits

Visit this url:

```

https://manivannanmurugavel.github.io/annotating-tool/spacy-ner-annotator/

```