distilbert-base-uncased-finetuned-ner

bchaipats/distilbert-base-uncased-finetuned-ner

distilbert-base-uncased-finetuned-ner is a token classification model from bchaipats. 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. --

Downloads · 30 days

1% of all-time downloads

All-time downloads

430

Public

Repo size

1.9 GB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin266 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Oct 22, 2022
Updated: Oct 22, 2022
SHA: 26e17c78

Try a prompt

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: 0.0627
Precision: 0.9248
Recall: 0.9367
F1: 0.9307
Accuracy: 0.9835

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
0.245	1.0	878	0.0708	0.9130	0.9196	0.9163	0.9810
0.0538	2.0	1756	0.0636	0.9220	0.9350	0.9285	0.9827
0.0297	3.0	2634	0.0627	0.9248	0.9367	0.9307	0.9835

Framework versions

Transformers 4.23.1
Pytorch 1.12.1
Datasets 2.6.0
Tokenizers 0.13.1

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Oct 22, 2022
Updated: Oct 22, 2022