readme: ---
  tags:
  - bert
  - adapterhub:dp/ud_ewt
  - adapter-transformers
  datasets:
  - universal_dependencies
  language:
  - en
  ---
  
  # Adapter `AdapterHub/bert-base-uncased-pf-ud_en_ewt` for bert-base-uncased
  
  An [adapter](https://adapterhub.ml) for the `bert-base-uncased` model that was trained on the [dp/ud_ewt](https://adapterhub.ml/explore/dp/ud_ewt/) dataset and includes a prediction head for dependency parsing.
  
  This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
  
  ## Usage
  
  First, install `adapter-transformers`:
  
  ```
  pip install -U adapter-transformers
  ```
  _Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](https://docs.adapterhub.ml/installation.html)_
  
  Now, the adapter can be loaded and activated like this:
  
  ```python
  from transformers import AutoModelWithHeads
  
  model = AutoModelWithHeads.from_pretrained("bert-base-uncased")
  adapter_name = model.load_adapter("AdapterHub/bert-base-uncased-pf-ud_en_ewt", source="hf", set_active=True)
  ```
  
  ## Architecture & Training
  
  This adapter was trained using adapter-transformer's example script for dependency parsing.
  See https://github.com/Adapter-Hub/adapter-transformers/tree/master/examples/dependency-parsing.
  
  
  ## Evaluation results
  
  Scores achieved by dependency parsing adapters on the test set of UD English EWT after training:
  
  | Model | UAS | LAS |
  | --- | --- | --- |
  | `bert-base-uncased` | 91.74 | 89.15 |
  | `roberta-base` | 91.43 | 88.43 |
  
  
  ## Citation
  
  <!-- Add some description here -->