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--- |
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tags: |
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- spacy |
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- token-classification |
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language: |
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- en |
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model-index: |
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- name: en_nerry_rel_trf_sentBert |
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results: |
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- task: |
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name: NER |
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type: token-classification |
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metrics: |
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- name: NER Precision |
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type: precision |
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value: 0.9259259259 |
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- name: NER Recall |
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type: recall |
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value: 1.0 |
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- name: NER F Score |
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type: f_score |
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value: 0.9615384615 |
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--- |
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RE with transformer (sentence bert) |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_nerry_rel_trf_sentBert` | |
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| **Version** | `2.1.0` | |
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| **spaCy** | `>=3.6.1,<3.7.0` | |
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| **Default Pipeline** | `transformer`, `ner`, `relation_extractor` | |
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| **Components** | `transformer`, `ner`, `relation_extractor` | |
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| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) | |
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| **Sources** | n/a | |
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| **License** | n/a | |
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| **Author** | [HjAnthony]() | |
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### Label Scheme |
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<details> |
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<summary>View label scheme (4 labels for 2 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `CRIME`, `PERSON`, `PROCECUTION` | |
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| **`relation_extractor`** | `INVOVLED_IN` | |
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</details> |
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### Accuracy |
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| Type | Score | |
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| --- | --- | |
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| `ENTS_F` | 96.15 | |
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| `ENTS_P` | 92.59 | |
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| `ENTS_R` | 100.00 | |
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| `REL_MICRO_P` | 88.24 | |
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| `REL_MICRO_R` | 100.00 | |
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| `REL_MICRO_F` | 93.75 | |
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| `TRANSFORMER_LOSS` | 0.00 | |
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| `RELATION_EXTRACTOR_LOSS` | 366.91 | |
