---
library_name: transformers
tags: []
---

# Model Card for Model ID

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SetFit/CR
{'micro': 0.901595744680851, 'macro': 0.8922009995738251, 'weighted': 0.9010032832777053}
SetFit/sst2
{'micro': 0.9203734211971444, 'macro': 0.9203422887733446, 'weighted': 0.9203396944046945}
SetFit/sst5
{'micro': 0.43936651583710407, 'macro': 0.41543751108645566, 'weighted': 0.4312698680247299}
AmazonScience/massive
{'micro': 0.3954270342972428, 'macro': 0.386758540904241, 'weighted': 0.3968475639919267}
stanfordnlp/imdb
positive ['negative', 'positive']
{'micro': 0.9466, 'macro': 0.9465995193956745, 'weighted': 0.9465993912345211}
SetFit/20_newsgroups
{'micro': 0.3883430695698354, 'macro': 0.3697801544810726, 'weighted': 0.37658673042441476}
SetFit/enron_spam
{'micro': 0.544, 'macro': 0.5432692307692308, 'weighted': 0.5431230769230769}
PolyAI/banking77
{'micro': 0.2623376623376623, 'macro': 0.29566833181387553, 'weighted': 0.2956683318138756}
takala/financial_phrasebank
{'micro': 0.7098056537102474, 'macro': 0.585169173529447, 'weighted': 0.6875727976631041}
ag_news
{'micro': 0.7493421052631579, 'macro': 0.7292800055299333, 'weighted': 0.7292800055299334}
dair-ai/emotion
{'micro': 0.548, 'macro': 0.46040686059760794, 'weighted': 0.5544195013346873}
MoritzLaurer/cap_sotu
{'micro': 0.3746, 'macro': 0.38022241408794133, 'weighted': 0.3746413725365648}
cornell-movie-review-data/rotten_tomatoes
{'micro': 0.801125703564728, 'macro': 0.8011145022582223, 'weighted': 0.8011145022582222}
Average Score: 0.5943268871385287

## Model Details

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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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