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README.md
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---
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library_name: keras-hub
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---
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## Model Overview
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FNet is a set of language models published by Google as part of the paper [FNet: Mixing Tokens with Fourier Transforms](https://arxiv.org/abs/2105.03824). FNet replaces the self-attention of BERT with an unparameterized fourier transform, dramatically lowering the number of trainable parameters in the model. FNet achieves training at 92-97% accuracy of BERT counterparts on GLUE benchmark, with faster training and much smaller saved checkpoints.
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preprocessor=None,
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)
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classifier.fit(x=features, y=labels, batch_size=2)
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```
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---
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library_name: keras-hub
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license: apache-2.0
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language:
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- en
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tags:
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- text-classification
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- keras
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---
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## Model Overview
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FNet is a set of language models published by Google as part of the paper [FNet: Mixing Tokens with Fourier Transforms](https://arxiv.org/abs/2105.03824). FNet replaces the self-attention of BERT with an unparameterized fourier transform, dramatically lowering the number of trainable parameters in the model. FNet achieves training at 92-97% accuracy of BERT counterparts on GLUE benchmark, with faster training and much smaller saved checkpoints.
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preprocessor=None,
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)
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classifier.fit(x=features, y=labels, batch_size=2)
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```
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