Introduction of distilbert-base-uncased-rotten-tomatoes
Model Details of distilbert-base-uncased-rotten-tomatoes
TextAttack Model Card
This `distilbert-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 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 classification task, the model was trained with a cross-entropy loss function.
The best score the model achieved on this task was 0.8395872420262664, as measured by the
eval set accuracy, found after 2 epochs.
For more information, check out [TextAttack on Github](https://github.com/QData/TextAttack).
Runs of textattack distilbert-base-uncased-rotten-tomatoes on huggingface.co
302
Total runs
-3
24-hour runs
-63
3-day runs
-65
7-day runs
-448
30-day runs
More Information About distilbert-base-uncased-rotten-tomatoes huggingface.co Model
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distilbert-base-uncased-rotten-tomatoes is an open source model from GitHub that offers a free installation service, and any user can find distilbert-base-uncased-rotten-tomatoes on GitHub to install. At the same time, huggingface.co provides the effect of distilbert-base-uncased-rotten-tomatoes install, users can directly use distilbert-base-uncased-rotten-tomatoes installed effect in huggingface.co for debugging and trial. It also supports api for free installation.
distilbert-base-uncased-rotten-tomatoes install url in huggingface.co: