covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess

sumba/covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess

covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess is a text classification model from sumba. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Aug 2, 2022
Updated: Aug 2, 2022
SHA: 67a0ba2a

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Model card

From the Hugging Face model README

covid-twitter-bert-v2-no_description-stance-loss-hyp-unprocess

This model is a fine-tuned version of digitalepidemiologylab/covid-twitter-bert-v2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5162
Accuracy: 0.0862

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1.4275469935864394e-05
train_batch_size: 8
eval_batch_size: 8
seed: 40
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.8058	1.0	632	0.5946	0.1411
0.5512	2.0	1264	0.5162	0.0862
0.4049	3.0	1896	0.6612	0.0470
0.1756	4.0	2528	0.7155	0.0426

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu102
Datasets 2.2.1
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: bert
License: mit
Created: Aug 2, 2022
Updated: Aug 2, 2022