Article_250v6_NER_Model_3Epochs_UNAUGMENTED

DOOGLAK/Article_250v6_NER_Model_3Epochs_UNAUGMENTED

Article_250v6_NER_Model_3Epochs_UNAUGMENTED is a token classification model from DOOGLAK. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

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

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Aug 11, 2022
Updated: Aug 11, 2022
SHA: 9c7ab7de

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Datasets

article250v6_wikigold_split

Model card

From the Hugging Face model README

Article_250v6_NER_Model_3Epochs_UNAUGMENTED

This model is a fine-tuned version of bert-base-cased on the article250v6_wikigold_split dataset. It achieves the following results on the evaluation set:

Loss: 0.3052
Precision: 0.3970
Recall: 0.3699
F1: 0.3830
Accuracy: 0.8863

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	29	0.5222	0.1785	0.0817	0.1121	0.8202
No log	2.0	58	0.3356	0.3575	0.3357	0.3462	0.8780
No log	3.0	87	0.3052	0.3970	0.3699	0.3830	0.8863

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu113
Datasets 2.4.0
Tokenizers 0.11.6

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Aug 11, 2022
Updated: Aug 11, 2022