test-ner

kSaluja/test-ner

test-ner is a token classification model from kSaluja. 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: May 6, 2022
Updated: May 6, 2022
SHA: ed3109f7

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Model card

From the Hugging Face model README

test-ner

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

Loss: 0.1014
Precision: 0.9609
Recall: 0.9574
F1: 0.9591
Accuracy: 0.9732

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	151	0.1848	0.9060	0.9184	0.9122	0.9490
No log	2.0	302	0.1137	0.9548	0.9529	0.9538	0.9705
No log	3.0	453	0.1014	0.9609	0.9574	0.9591	0.9732

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 6, 2022
Updated: May 6, 2022