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distilbert-base-uncased_sts_mrpc_pfeiffer
AdapterHub/distilbert-base-uncased_sts_mrpc_pfeiffer
distilbert-base-uncased_sts_mrpc_pfeiffer is a text classification model from AdapterHub. Use it when you need a label for a piece of text. It is set up for adapter-transformers. The card lists the license as apache-2.0.
Adapter for distilbert-base-uncased in Pfeiffer architecture trained on the MRPC dataset for 15 epochs with early stopping and a learning rate of 1e-4.
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At a glance
- Task
- Text Classification
- Library
- adapter-transformers
- License
- apache-2.0
- Access
- Public
- Created
- May 5, 2024
- Updated
- May 5, 2024
- SHA
- 1e8d18ca
Try a prompt
Model card
From the Hugging Face model README
Adapter distilbert-base-uncased_sts_mrpc_pfeiffer for distilbert-base-uncased
Adapter for distilbert-base-uncased in Pfeiffer architecture trained on the MRPC dataset for 15 epochs with early stopping and a learning rate of 1e-4.
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("distilbert-base-uncased")
adapter_name = model.load_adapter("AdapterHub/distilbert-base-uncased_sts_mrpc_pfeiffer")
model.set_active_adapters(adapter_name)
Architecture & Training
- Adapter architecture: pfeiffer
- Prediction head: classification
- Dataset: MRPC
Author Information
- Author name(s): Clifton Poth
- Author email: [email protected]
- Author links: Website, GitHub, Twitter
Citation
This adapter has been auto-imported from https://github.com/Adapter-Hub/Hub/blob/master/adapters/ukp/distilbert-base-uncased_sts_mrpc_pfeiffer.yaml.
- Task
- Text Classification
- Library
- adapter-transformers
- License
- apache-2.0
- Created
- May 5, 2024
- Updated
- May 5, 2024