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@@ -89,36 +89,17 @@ This model is designed for information extraction from resumes/CVs written in En
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  | `Spacy Components` | Transformer, Named Entity Recognition (NER) |
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  | `Author` | [Youssef Chafiqui](https://huggingface.co/ychafiqui) |
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- **Language:** English
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- **Task:** Information extraction from resumes/CVs
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- **Components:** Transformer, Named Entity Recognition (NER)
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- **Author:** [Youssef Chafiqui](https://huggingface.co/ychafiqui)
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  ### Labels
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  The model recognizes various labels corresponding to different sections of a resume. Below are some of the labels used by the model:
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- **ADDRESS:**
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- **CERTIFICATION:**
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- **EDUCATION:**
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- **EMAIL:**
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- **EXPERIENCE:**
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- **FNAME:**
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- **HOBBY:**
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- **HSKILL:**
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- **LANGUAGE:**
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- **LNAME:**
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- **PHONE:**
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- **PROFILE:**
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- **PROJECT:**
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- **SSKILL:**
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  ### Evaluation Metrics
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  | Type | Score |
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  | --- | --- |
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- | `NER F1 score` | 81.98 |
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- | `NER Precision` | 83.33 |
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- | `NER Recall` | 80.68 |
 
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  | `Spacy Components` | Transformer, Named Entity Recognition (NER) |
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  | `Author` | [Youssef Chafiqui](https://huggingface.co/ychafiqui) |
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  ### Labels
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  The model recognizes various labels corresponding to different sections of a resume. Below are some of the labels used by the model:
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+ | Labels | Description |
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+ | --- | --- |
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+ | FNAME | First name |
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+ | `LNAME` | Last name |
 
 
 
 
 
 
 
 
 
 
 
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  ### Evaluation Metrics
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  | Type | Score |
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  | --- | --- |
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+ | `F1 score` | 81.98 |
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+ | `Precision` | 83.33 |
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+ | `Recall` | 80.68 |