| --- |
| tags: |
| - spacy |
| - token-classification |
| language: |
| - nl |
| model-index: |
| - name: nl_ner |
| results: |
| - task: |
| name: NER |
| type: token-classification |
| metrics: |
| - name: NER Precision |
| type: precision |
| value: 0.5 |
| - name: NER Recall |
| type: recall |
| value: 0.4 |
| - name: NER F Score |
| type: f_score |
| value: 0.4444444444 |
| --- |
| | Feature | Description | |
| | --- | --- | |
| | **Name** | `nl_ner` | |
| | **Version** | `0.0.0` | |
| | **spaCy** | `>=3.6.1,<3.7.0` | |
| | **Default Pipeline** | `tok2vec`, `ner` | |
| | **Components** | `tok2vec`, `ner` | |
| | **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
| | **Sources** | n/a | |
| | **License** | n/a | |
| | **Author** | [n/a]() | |
|
|
| ### Description |
|
|
| Voor meer info: https://github.com/RaThorat/my-chatbot-project |
|
|
| Prodigy (ner.manual) is gebruikt om te annoteren van entiteiten zoals: PERSOON, ORGANISATIE, PROJECT, BEDRAG, LOCATIE, TIJDSPERIODE, SUBSIDIE. |
|
|
| prodigy ner.manual ner_dataset nl_core_news_lg ./Data/combined_documents.txt --label PERSOON,ORG,PROJECT,BEDRAG,LOC,TIJD,SUB |
| |
| prodigy train ./models --ner ner_dataset --lang nl --label-stats --verbose --eval-split 0.1 |
|
|
| 46 documenten (https://github.com/RaThorat/my-chatbot-project/tree/main/Data/txt) uit de DUS-i website gedownload, schoongemaakt, samengesteld in combined_documents.txt |
| |
| ### Label Scheme |
| |
| <details> |
| |
| <summary>View label scheme (7 labels for 1 components)</summary> |
| |
| | Component | Labels | |
| | --- | --- | |
| | **`ner`** | `BEDRAG`, `LOC`, `ORG`, `PERSOON`, `PROJECT`, `SUB`, `TIJD` | |
| |
| </details> |
| |
| ### Accuracy |
| |
| | Type | Score | |
| | --- | --- | |
| | `ENTS_F` | 44.44 | |
| | `ENTS_P` | 50.00 | |
| | `ENTS_R` | 40.00 | |
| | `TOK2VEC_LOSS` | 6462.80 | |
| | `NER_LOSS` | 14799.70 | |
