---
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 |