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AdapterHub/roberta-base-pf-ud_en_ewt
roberta-base-pf-ud_en_ewt is a machine learning model from AdapterHub. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for adapter-transformers.
An adapter for the roberta-base model that was trained on the dp/udewt dataset and includes a prediction head for dependency parsing.
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From the Hugging Face model README
AdapterHub/roberta-base-pf-ud_en_ewt for roberta-baseAn 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)
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.
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 |