en_Spacy_Custom_ner / README.md
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---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_Spacy_Custom_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9918793503
- name: NER Recall
type: recall
value: 0.9965034965
- name: NER F Score
type: f_score
value: 0.9941860465
---
| Feature | Description |
| --- | --- |
| **Name** | `en_Spacy_Custom_ner` |
| **Version** | `0.0.0` |
| **spaCy** | `>=3.5.3,<3.6.0` |
| **Default Pipeline** | `tok2vec`, `ner` |
| **Components** | `tok2vec`, `ner` |
| **Vectors** | 514157 keys, 514157 unique vectors (300 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |
### Label Scheme
<details>
<summary>View label scheme (16 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `AGENT_FALLBACK`, `BOOK`, `COMODITY`, `CONTAINER COUNT`, `CONTAINER SIZE`, `CONTAINER SIZE-COUNT`, `DESTINATION`, `ENQUIRY`, `HELP`, `INCOTERM`, `KYC`, `ORIGIN`, `SEARCH RATES`, `SHIP`, `SHIPMENT TYPE`, `WELCOME_MSG` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 99.42 |
| `ENTS_P` | 99.19 |
| `ENTS_R` | 99.65 |
| `TOK2VEC_LOSS` | 1794.25 |
| `NER_LOSS` | 53209.43 |