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--- |
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tags: |
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- spacy |
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- token-classification |
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- text-classification |
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language: |
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- en |
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model-index: |
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- name: en_generic_big |
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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: 0.9469753547 |
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- name: NER Recall |
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type: recall |
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value: 0.9399555226 |
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- name: NER F Score |
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type: f_score |
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value: 0.943452381 |
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--- |
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| Feature | Description | |
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| --- | --- | |
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| **Name** | `en_generic_big` | |
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| **Version** | `0.0.1` | |
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| **spaCy** | `>=3.7.5,<3.8.0` | |
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| **Default Pipeline** | `tok2vec`, `ner`, `textcat` | |
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| **Components** | `tok2vec`, `ner`, `textcat` | |
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| **Vectors** | 514157 keys, 514157 unique vectors (300 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 (35 labels for 2 components)</summary> |
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| Component | Labels | |
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| --- | --- | |
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| **`ner`** | `AGE`, `BRAND`, `CLOCK_SPEED`, `COLOR`, `CORE_COUNT`, `DECORATION`, `FEATURE`, `FIT`, `GENDER`, `GRAPHICS`, `GRAPHICS_RAM`, `MATERIAL`, `MEASUREMENT`, `MEASUREMENT_AREA`, `MEM_TYPE`, `MODEL_NUMBER`, `NECKLINE`, `OPERATING_SYSTEM`, `PROCESSOR`, `PROCESSOR_MODEL`, `PRODUCT_SERIES`, `RAM`, `RESOLUTION`, `SCREEN_SIZE`, `SCREEN_TYPE`, `SIZE`, `SLEEVE`, `STORAGE`, `STORAGE_TYPE`, `TAG`, `TYPE`, `ZIP` | |
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| **`textcat`** | `212`, `297`, `328` | |
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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` | 94.35 | |
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| `ENTS_P` | 94.70 | |
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| `ENTS_R` | 94.00 | |
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| `CATS_SCORE` | 100.00 | |
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| `CATS_MICRO_P` | 100.00 | |
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| `CATS_MICRO_R` | 100.00 | |
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| `CATS_MICRO_F` | 100.00 | |
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| `CATS_MACRO_P` | 100.00 | |
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| `CATS_MACRO_R` | 100.00 | |
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| `CATS_MACRO_F` | 100.00 | |
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| `CATS_MACRO_AUC` | 100.00 | |
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| `TOK2VEC_LOSS` | 28927.81 | |
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| `NER_LOSS` | 63903.29 | |
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| `TEXTCAT_LOSS` | 0.08 | |
