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https://api-inference.huggingface.co/models/textattack/bert-base-cased-STS-B
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textattack/bert-base-cased-STS-B textattack/bert-base-cased-STS-B
35 downloads
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pytorch

tf

Contributed by

TextAttack
2 team members · 82 models

How to use this model directly from the 🤗/transformers library:

			
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from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-cased-STS-B") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-cased-STS-B")
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TextAttack Model Card

This `bert-base-cased` model was fine-tuned for sequence classificationusing TextAttack 
and the glue dataset loaded using the `nlp` library. The model was fine-tuned 
for 3 epochs with a batch size of 128, a learning 
rate of 1e-05, and a maximum sequence length of 128. 
Since this was a regression task, the model was trained with a mean squared error loss function. 
The best score the model achieved on this task was 0.8244429996636282, as measured by the 
eval set pearson correlation, found after 2 epochs.

For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack).