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bert-base-uncased-ag-news
textattack/bert-base-uncased-ag-news
bert-base-uncased-ag-news is a text classification model from textattack. Use it when you need a label for a piece of text. It is set up for transformers.
and the agnews dataset loaded using the nlp library. The model was fine-tuned for 5 epochs with a batch size of 16, a learning rate of 3e-05, and a maximum sequence length of 128. Since this was a classification task,…
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- May 20, 2021
- SHA
- fe417ad6
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Model card
From the Hugging Face model README
TextAttack Model CardThis bert-base-uncased model was fine-tuned for sequence classification using TextAttack
and the ag_news dataset loaded using the nlp library. The model was fine-tuned
for 5 epochs with a batch size of 16, 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 0.9514473684210526, as measured by the
eval set accuracy, found after 3 epochs.
For more information, check out TextAttack on Github.
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Hf Inference
- live
- Created
- Mar 2, 2022
- Updated
- May 20, 2021