address_parsing_test_1

Hasanmurad/address_parsing_test_1

address_parsing_test_1 is a token classification model from Hasanmurad. Use it when you need labels on individual words, such as names. It is set up for transformers.

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

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At a glance

Task: Token Classification
Library: transformers
Model type: electra
Access: Public
Created: Nov 25, 2022
Updated: Nov 25, 2022
SHA: c25b5ef9

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Model card

From the Hugging Face model README

address_parsing_test_1

This model is a fine-tuned version of csebuetnlp/banglabert on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0207
Precision: 0.9953
Recall: 0.9957
F1: 0.9955
Accuracy: 0.9963

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: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0669	1.0	1266	0.0168	0.9890	0.9913	0.9902	0.9937
0.02	2.0	2532	0.0132	0.9953	0.9961	0.9957	0.9967
0.0122	3.0	3798	0.0177	0.9949	0.9955	0.9952	0.9962
0.0068	4.0	5064	0.0181	0.9951	0.9957	0.9954	0.9963
0.0048	5.0	6330	0.0207	0.9953	0.9957	0.9955	0.9963

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: electra
Created: Nov 25, 2022
Updated: Nov 25, 2022