ner-distilbert

textminr/ner-distilbert

ner-distilbert is a token classification model from textminr. 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: distilbert
Access: Public
Created: Dec 30, 2023
Updated: Jan 11, 2024
SHA: c21d8c0d

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Base models

Model card

From the Hugging Face model README

ner-distilbert

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

Loss: 0.0003
Precision: 0.9988
Recall: 0.9980
F1: 0.9984
Accuracy: 0.9998

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0002	0.16	250	0.0011	0.9961	0.9980	0.9971	0.9996
0.0001	0.31	500	0.0008	0.9977	0.9977	0.9977	0.9997
0.0004	0.47	750	0.0005	0.9992	0.9977	0.9984	0.9998
0.0002	0.63	1000	0.0005	0.9984	0.9977	0.9980	0.9997
0.0002	0.79	1250	0.0003	0.9988	0.9980	0.9984	0.9998
0.0	0.94	1500	0.0003	0.9988	0.9980	0.9984	0.9998

Framework versions

Transformers 4.34.0
Pytorch 2.1.0
Datasets 2.14.5
Tokenizers 0.14.1

Task: Token Classification
Library: transformers
Type: distilbert
Created: Dec 30, 2023
Updated: Jan 11, 2024