Overview
In the Comparing Models notebook, we’re evaluating en.sentiment.imdb.glove
model from JSL and lvwerra/distilbert-imdb
from HF which are models trained for text classification task. The notebook showcases how we can get a view of how the models compare. The final report output is different than normal and includes both models’s results.
Open in Collab
Category | Hub | Task | Open In Colab |
---|---|---|---|
Multiple Model Comparison | Hugging Face/John Snow Labs/Spacy | NER/Text-Classification |
Config Used
tests:
defaults:
min_pass_rate: 1.0
robustness:
add_typo:
min_pass_rate: 0.7
american_to_british:
min_pass_rate: 0.7
accuracy:
min_micro_f1_score:
min_score: 0.7
bias:
replace_to_female_pronouns:
min_pass_rate: 0.7
replace_to_low_income_country:
min_pass_rate: 0.7
fairness:
min_gender_f1_score:
min_score: 0.6
representation:
min_label_representation_count:
min_count: 50