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<!DOCTYPE html> |
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<meta charset="UTF-8" /> |
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<meta name="viewport" content="width=device-width, initial-scale=1.0" /> |
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<title>SpaCy NER Training Guide</title> |
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h2 { |
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margin-bottom: 30px; |
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</head> |
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<body> |
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<div class="container"> |
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<h1>SpaCy NER Model Training Guide</h1> |
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<div class="step"> |
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<h2>Step 1: Upload Your Resume File</h2> |
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<p> |
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Upload a resume or document file for text extraction. Supported |
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formats include: |
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</p> |
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<ul> |
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<li>PDF</li> |
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<li>DOCX (Word Document)</li> |
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<li>RSF (Rich Structured Format)</li> |
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<li>ODT (Open Document Text)</li> |
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<li>PNG, JPG, JPEG (Image Formats)</li> |
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<li>JSON</li> |
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</ul> |
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<p> |
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Ensure that your file is in one of the supported formats before |
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uploading. The system will extract and process the text from your |
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document automatically. |
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</p> |
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<a href="{{ url_for('index') }}" class="btn btn-primary" |
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>Proceed to Upload</a |
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> |
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</div> |
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<div class="step"> |
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<h2>Step 2: Preview and Edit Extracted Text</h2> |
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<p> |
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After uploading your document, you will be shown a preview of the |
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extracted text. This preview allows you to edit the text if needed to |
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correct any extraction errors or remove unwanted content. Once you're |
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satisfied, click "Next" to proceed to Named Entity Recognition (NER) |
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annotations. |
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</p> |
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<a href="{{ url_for('text_preview') }}" class="btn btn-primary" |
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>Proceed to Text Preview</a |
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> |
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</div> |
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<div class="step"> |
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<h2>Step 3: Annotate Named Entities</h2> |
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<p> |
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In this step, you will preview the Named Entity Recognition (NER) |
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results generated from your text. You can add new entity labels, |
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select relevant text for each label, and make manual adjustments. Once |
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you’ve annotated the text with the appropriate labels, save your |
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annotations and export the data in JSON format for model training. |
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NOTE:(following labels can be taken in use: ["ABOUT","CERTIFICATE", |
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"COMPANY","CONTACT","COURSE", "DOB", "EMAIL", "EXPERIENCE", "HOBBIES", |
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"INSTITUTE", "JOB_TITLE", "LANGUAGE", "LAST_QUALIFICATION_YEAR", "LINK", |
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"LOCATION", "PERSON", "PROJECTS", "QUALIFICATION", "SCHOOL", "SKILL", |
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"SOFT_SKILL", "UNIVERSITY", "YEARS_EXPERIENCE"] |
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</p> |
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<p>Instructions:</p> |
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<ul> |
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<li>Click "Begin!" to load the extracted text.</li> |
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<li> |
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Highlight sections of the text and assign them to the available |
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labels. |
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</li> |
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<li>Add new labels if necessary.</li> |
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<li> |
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Once done, click "Export" to download your annotations as a JSON |
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file. |
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</li> |
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</ul> |
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<a href="{{ url_for('ner_preview') }}" class="btn btn-primary" |
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>Proceed to NER Annotation</a |
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> |
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</div> |
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<div class="step"> |
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<h2>Step 4: Save and Format JSON Data</h2> |
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<p> |
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Upload your annotated JSON file from the previous step. The system |
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will process and reformat the JSON file to ensure compatibility with |
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the SpaCy model training process. After formatting, you can proceed to |
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the model training step. |
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</p> |
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<p>Instructions:</p> |
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<ul> |
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<li> |
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Upload the JSON file you downloaded after the annotation step. |
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</li> |
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<li>Click "Process" to reformat the file.</li> |
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<li> |
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Once processing is complete, click "Next" to proceed with training. |
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</li> |
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</ul> |
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<a href="{{ url_for('json_file') }}" class="btn btn-primary" |
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>Proceed to Save JSON</a |
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> |
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</div> |
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<div class="step"> |
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<h2>Step 5: Train the NER Model</h2> |
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<p> |
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In this final step, you will convert the formatted JSON data into the |
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SpaCy format and begin training the NER model. You can customize the |
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training by selecting the number of epochs (iterations) the model will |
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go through and setting the version for the trained model. |
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</p> |
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<p>Guidelines:</p> |
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<ul> |
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<li> |
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Number of epochs: The higher the number of epochs, the more times |
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the model will learn from the data, but too many epochs can lead to |
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overfitting. Start with 10 epochs for a balanced training approach. |
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</li> |
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<li> |
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Model versioning: Provide a version name for this training session, |
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so you can keep track of different versions of the model. |
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</li> |
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</ul> |
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<p> |
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Once the training is complete, you can download the latest version of |
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the trained model for use in production. |
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</p> |
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<a href="{{ url_for('spacy_file') }}" class="btn btn-primary" |
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>Proceed to Model Training</a |
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> |
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</div> |
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