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Task Adapters

Pre-trained model:

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bert bart xlm-roberta distilbert gpt2 roberta mbart

STS-B

The Semantic Textual Similarity Benchmark is a collection of sentence pairs drawn from news headlines and other sources. They were annotated with a score from 1 to 5 denoting how similar the two sentences are in terms of semantic meaning.
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sts/sts-b@ukp gpt2
1 version Architecture: pfeiffer non-linearity: relu reduction factor: 16 Head: 

Adapter for gpt2 in Pfeiffer architecture trained on the STS-B dataset for 10 epochs with a learning rate of 1e-4.

sts/sts-b@ukp gpt2
1 version Architecture: houlsby non-linearity: swish reduction factor: 16 Head: 

Adapter for gpt2 in Houlsby architecture trained on the STS-B dataset for 10 epochs with a learning rate of 1e-4.

sts/sts-b@ukp roberta-base
1 version Architecture: houlsby Head: 

STS-B adapter (with head) trained using the `run_glue.py` script with an extension that retains the best checkpoint (out of 30 epochs).

sts/sts-b@ukp facebook/bart-base
1 version Architecture: houlsby non-linearity: swish reduction factor: 16 Head: 

Adapter for bart-base in Houlsby architecture trained on the STS-B dataset for 15 epochs with early stopping and a learning rate of 1e-4.

sts/sts-b@ukp distilbert-base-uncased
1 version Architecture: houlsby Head: 

Adapter for distilbert-base-uncased in Houlsby architecture trained on the STS-B dataset for 15 epochs with early stopping and a learning rate of 1e-4.

sts/sts-b@ukp roberta-large
1 version Architecture: pfeiffer Head: 

STS-B adapter (with head) trained using the `run_glue.py` script with an extension that retains the best checkpoint (out of 30 epochs).

sts/sts-b@ukp roberta-large
1 version Architecture: houlsby Head: 

STS-B adapter (with head) trained using the `run_glue.py` script with an extension that retains the best checkpoint (out of 30 epochs).

sts/sts-b@ukp facebook/bart-base
1 version Architecture: pfeiffer non-linearity: relu reduction factor: 16 Head: 

Adapter for bart-base in Pfeiffer architecture trained on the STS-B dataset for 15 epochs with early stopping and a learning rate of 1e-4.

sts/sts-b@ukp bert-base-uncased
1 version Architecture: houlsby Head: 

Adapter in Houlsby architecture trained on the STS-Benchmark task for 20 epochs with early stopping and a learning rate of 1e-4. See https://arxiv.org/pdf/2007.07779.pdf.

sts/sts-b@ukp bert-base-uncased
1 version Architecture: pfeiffer Head: 

Adapter in Pfeiffer architecture trained on the STS-Benchmark task for 20 epochs with early stopping and a learning rate of 1e-4. See https://arxiv.org/pdf/2007.07779.pdf.

sts/sts-b@ukp distilbert-base-uncased
1 version Architecture: pfeiffer Head: 

Adapter for distilbert-base-uncased in Pfeiffer architecture trained on the STS-B dataset for 15 epochs with early stopping and a learning rate of 1e-4.

sts/sts-b@ukp roberta-base
1 version Architecture: pfeiffer Head: 

STS-B adapter (with head) trained using the `run_glue.py` script with an extension that retains the best checkpoint (out of 30 epochs).

AdapterHub/bert-base-uncased-pf-stsb bert-base-uncased
huggingface.co Head: 

# Adapter `AdapterHub/bert-base-uncased-pf-stsb` for bert-base-uncased An [adapter](https://adapterhub.ml) for the `bert-base-uncased` model that was trained on the...

AdapterHub/roberta-base-pf-stsb roberta-base
huggingface.co Head: 

# Adapter `AdapterHub/roberta-base-pf-stsb` for roberta-base An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the...

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