Upload README.md
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README.md
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- task:
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name: NER
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type: token-classification
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### Label Scheme
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<details>
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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: 0.8990228013
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- name: NER Recall
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type: recall
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value: 0.9019607843
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- name: NER F Score
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type: f_score
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value: 0.9004893964
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---
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| Feature | Description |
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| --- | --- |
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| **Name** | `nerIta` |
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| **Version** | `0.0.0` |
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| **spaCy** | `>=3.2.1,<3.3.0` |
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| **Default Pipeline** | `transformer`, `ner` |
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| **Components** | `transformer`, `ner` |
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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** | [n/a]() |
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### Label Scheme
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<details>
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<summary>View label scheme (18 labels for 1 components)</summary>
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| Component | Labels |
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| --- | --- |
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| **`ner`** | `BRAND`, `FOOD PRODUCT`, `INGREDIENT`, `MEASURE`, `QUANTITY` |
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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` | 90.05 |
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| `ENTS_P` | 89.90 |
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| `ENTS_R` | 90.20 |
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| `TOK2VEC_LOSS` | 65769.53 |
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| `NER_LOSS` | 7865.95 |
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