distilbert-base-uncased-finetuned-ner

yam1ke/distilbert-base-uncased-finetuned-ner

distilbert-base-uncased-finetuned-ner is a token classification model from yam1ke. 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: distilbert
Access: Public
Created: Jul 9, 2022
Updated: Jul 10, 2022
SHA: 9c1be937

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Datasets

conll2003

Model card

From the Hugging Face model README

distilbert-base-uncased-finetuned-ner

This model is a fine-tuned version of distilbert-base-uncased on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.0607
Precision: 0.9285
Recall: 0.9362
F1: 0.9324
Accuracy: 0.9839

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: 16
eval_batch_size: 16
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
0.2452	1.0	878	0.0709	0.9184	0.9206	0.9195	0.9803
0.0501	2.0	1756	0.0621	0.9212	0.9328	0.9270	0.9830
0.0299	3.0	2634	0.0607	0.9285	0.9362	0.9324	0.9839

Framework versions

Transformers 4.20.1
Pytorch 1.12.0
Datasets 2.3.2
Tokenizers 0.12.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Jul 9, 2022
Updated: Jul 10, 2022