Downloads · 30 days
23
1% of all-time downloads
albert-base-v2-rotten-tomatoes
textattack/albert-base-v2-rotten-tomatoes
albert-base-v2-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 albert-base-v2 model was fine-tuned for sequence classification using TextAttack and the rottentomatoes dataset loaded using the nlp library. The model was fine-tuned for 5 epochs with a batch size of 64, a learn…
All-time downloads
4.2K
Public
Repo size
94.3 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin46.7 MB · 98%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- albert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Jul 6, 2020
- SHA
- b19b7cd9
Try a prompt
Model card
From the Hugging Face model README
TextAttack Model Card
This albert-base-v2 model was fine-tuned for sequence classification using TextAttack
and the rotten_tomatoes dataset loaded using the nlp library. The model was fine-tuned
for 5 epochs with a batch size of 64, 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 0.8808630393996247, as measured by the
eval set accuracy, found after 1 epoch.
For more information, check out TextAttack on Github.
- Task
- Text Classification
- Library
- transformers
- Type
- albert
- Created
- Mar 2, 2022
- Updated
- Jul 6, 2020