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text-generation mask_token: <mask>
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https://api-inference.huggingface.co/models/textattack/xlnet-base-cased-RTE
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textattack/xlnet-base-cased-RTE textattack/xlnet-base-cased-RTE
24 downloads
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pytorch

tf

Contributed by

TextAttack
3 team members · 84 models

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

			
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from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("textattack/xlnet-base-cased-RTE") model = AutoModelWithLMHead.from_pretrained("textattack/xlnet-base-cased-RTE")
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TextAttack Model Card

This xlnet-base-cased model was fine-tuned for sequence classification using TextAttack and the glue dataset loaded using the nlp library. The model was fine-tuned for 5 epochs with a batch size of 16, a learning rate of 2e-05, and a maximum sequence length of 128. Since this was a classification task, the model was trained with a cross-entropy loss function. The best score the model achieved on this task was 0.7111913357400722, as measured by the eval set accuracy, found after 3 epochs.

For more information, check out TextAttack on Github.