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---
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_deberta_v3_base_ner_method
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.814
- name: NER Recall
type: recall
value: 0.8075396825
- name: NER F Score
type: f_score
value: 0.8107569721
base_model:
- microsoft/deberta-v3-base
pipeline_tag: token-classification
---
| Feature | Description |
| --- | --- |
| **Name** | `en_deberta_v3_base_ner_method` |
| **Version** | `0.1.0` |
| **spaCy** | `>=3.8.7,<3.9.0` |
| **Default Pipeline** | `transformer`, `ner` |
| **Components** | `transformer`, `ner` |
| **Vectors** | 0 keys, 0 unique vectors (0 dimensions) |
| **Sources** | n/a |
| **License** | n/a |
| **Author** | [n/a]() |
### Label Scheme
<details>
<summary>View label scheme (1 labels for 1 components)</summary>
| Component | Labels |
| --- | --- |
| **`ner`** | `METHOD` |
</details>
### Accuracy
| Type | Score |
| --- | --- |
| `ENTS_F` | 81.08 |
| `ENTS_P` | 81.40 |
| `ENTS_R` | 80.75 |
| `TRANSFORMER_LOSS` | 104931.78 |
| `NER_LOSS` | 178344.87 | |