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https://api-inference.huggingface.co/models/textattack/albert-base-v2-CoLA
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textattack/albert-base-v2-CoLA textattack/albert-base-v2-CoLA
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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/albert-base-v2-CoLA") model = AutoModelForSequenceClassification.from_pretrained("textattack/albert-base-v2-CoLA")
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TextAttack Model Cardand the glue dataset loaded using the nlp library. The model was fine-tuned

for 5 epochs with a batch size of 32, a learning rate of 3e-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 0.8245445829338447, as measured by the eval set accuracy, found after 2 epochs.

For more information, check out TextAttack on Github.