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Task Adapters

Pre-trained model:

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bert bart xlm-roberta distilbert gpt2 roberta mbart

RTE

Recognizing Textual Entailment is a binary entailment task similar to MNLI, but with much less training data.
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nli/rte@ukp distilbert-base-uncased
1 version Architecture: houlsby Head: 

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

nli/rte@ukp bert-base-uncased
1 version Architecture: houlsby Head: 

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

nli/rte@ukp bert-base-uncased
1 version Architecture: pfeiffer Head: 

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

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

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

nli/rte@ukp roberta-base
1 version Architecture: pfeiffer Head: 

Pfeiffer Adapter trained on RTE.

nli/rte@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 RTE dataset for 15 epochs with early stopping and a learning rate of 1e-4.

nli/rte@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 RTE dataset for 15 epochs with early stopping and a learning rate of 1e-4.

nli/rte@ukp distilbert-base-uncased
1 version Architecture: pfeiffer Head: 

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

nli/rte@ukp gpt2
1 version Architecture: pfeiffer non-linearity: relu reduction factor: 16 Head: 

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

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

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

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

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

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