Adapter facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer for facebook/mbart-large-cc25

Adapter for mbart-large-cc25 in Pfeiffer architecture with reduction factor 2 trained on the WMT16 Romanian-English translation task. Training for 10 epochs with early stopping and a learning rate of 1e-4. After post-processing following https://github.com/huggingface/transformers/blob/master/examples/legacy/seq2seq/romanian_postprocessing.md, it achieves a BLEU score of 36.3.

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

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

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("facebook/mbart-large-cc25")
adapter_name = model.load_adapter("AdapterHub/facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer")
model.set_active_adapters(adapter_name)

Architecture & Training

• Adapter architecture: pfeiffer
• Prediction head: seq2seq lm
• Dataset: WMT16 English-Romanian

Author Information

• Author name(s): Clifton Poth
• Author email: calpt@mail.de
• Author links: Website, GitHub, Twitter

Citation

This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/facebook-mbart-large-cc25_translation_wmt16_ro_en_pfeiffer.yaml.