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bert-base-uncased-rotten-tomatoes
textattack/bert-base-uncased-rotten-tomatoes
bert-base-uncased-rotten-tomatoes 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.
This bert-base-uncased model was fine-tuned for sequence classificationusing TextAttack and the rottentomatoes dataset loaded using the nlp library. The model was fine-tuned for 10 epochs with a batch size of 16, a le…
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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
- 2aeb2b03
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Model card
From the Hugging Face model README
TextAttack Model Card
This `bert-base-uncased` model was fine-tuned for sequence classificationusing TextAttack
and the rotten_tomatoes dataset loaded using the `nlp` library. The model was fine-tuned
for 10 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 0.875234521575985, as measured by the
eval set accuracy, found after 4 epochs.
For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack).
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- May 20, 2021