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Adapter AdapterHub/roberta-base-pf-ud_en_ewt for roberta-base

An adapter for the roberta-base model that was trained on the dp/ud_ewt dataset and includes a prediction head for dependency parsing.

This adapter was created for usage with the adapter-transformers library.


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

Now, the adapter can be loaded and activated like this:

from transformers import AutoModelWithHeads

model = AutoModelWithHeads.from_pretrained("roberta-base")
adapter_name = model.load_adapter("AdapterHub/roberta-base-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:

bert-base-uncased 91.74 89.15
roberta-base 91.43 88.43


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Dataset used to train AdapterHub/roberta-base-pf-ud_en_ewt