ner-deBERTa-v3-large-conll2003

alphaduriendur/ner-deBERTa-v3-large-conll2003

ner-deBERTa-v3-large-conll2003 is a token classification model from alphaduriendur. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.

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

Downloads · 30 days

29% of all-time downloads

All-time downloads

Public

Parameters

434M

10.4 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.bin1.7 GB · 50%

Parameter types

How the weights are stored.

F32434M · 100%

Try a prompt

Datasets

conll2003

Model card

From the Hugging Face model README

ner-deBERTa-v3-large-conll2003

This model is a fine-tuned version of microsoft/deberta-v3-large on the conll2003 dataset. It achieves the following results on the evaluation set:

Loss: 0.1546
Precision: 0.9235
Recall: 0.9363
F1: 0.9298
Accuracy: 0.9853

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: cosine
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0077	1.0	878	0.1280	0.9096	0.9265	0.9180	0.9832
0.0084	2.0	1756	0.1380	0.9167	0.9299	0.9233	0.9844
0.0037	3.0	2634	0.1495	0.9221	0.9347	0.9283	0.9850
0.0015	4.0	3512	0.1517	0.9215	0.9347	0.9280	0.9849
0.0006	5.0	4390	0.1546	0.9235	0.9363	0.9298	0.9853

Framework versions

Transformers 4.30.2
Pytorch 2.0.1+cu118
Datasets 2.13.1
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: deberta-v2
License: mit
Created: Jul 3, 2023
Updated: Jul 3, 2023