distilbert-base-uncased-ner

douglasadams11/distilbert-base-uncased-ner

distilbert-base-uncased-ner is a token classification model from douglasadams11. 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: Dec 25, 2023
Updated: Dec 26, 2023
SHA: 46c75362

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Base models

Model card

From the Hugging Face model README

distilbert-base-uncased-ner

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

Loss: 0.1419
Precision: 0.9526
Recall: 0.9431
F1: 0.9479
Accuracy: 0.9434

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: 32
eval_batch_size: 32
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
0.2866	0.14	500	0.1970	0.9329	0.9213	0.9271	0.9212
0.198	0.28	1000	0.1851	0.9412	0.9218	0.9314	0.9253
0.1892	0.43	1500	0.1772	0.9431	0.9250	0.9340	0.9280
0.179	0.57	2000	0.1697	0.9440	0.9296	0.9367	0.9313
0.1719	0.71	2500	0.1618	0.9453	0.9330	0.9391	0.9339
0.1718	0.85	3000	0.1587	0.9443	0.9351	0.9397	0.9351
0.1664	0.99	3500	0.1569	0.9486	0.9340	0.9412	0.9361
0.1504	1.14	4000	0.1566	0.9480	0.9356	0.9417	0.9368
0.1479	1.28	4500	0.1539	0.9492	0.9369	0.9430	0.9381
0.1467	1.42	5000	0.1501	0.9499	0.9383	0.9441	0.9391
0.1478	1.56	5500	0.1489	0.9513	0.9368	0.9440	0.9390
0.147	1.7	6000	0.1457	0.9503	0.9402	0.9452	0.9407
0.1453	1.85	6500	0.1447	0.9510	0.9408	0.9459	0.9412
0.1384	1.99	7000	0.1442	0.9521	0.9405	0.9463	0.9415
0.1325	2.13	7500	0.1446	0.9494	0.9441	0.9467	0.9425
0.13	2.27	8000	0.1467	0.9524	0.9403	0.9463	0.9416
0.1286	2.41	8500	0.1435	0.9501	0.9440	0.9470	0.9427
0.1311	2.56	9000	0.1446	0.9529	0.9417	0.9473	0.9427
0.1258	2.7	9500	0.1438	0.9528	0.9425	0.9476	0.9431
0.1257	2.84	10000	0.1437	0.9527	0.9431	0.9479	0.9434
0.1289	2.98	10500	0.1420	0.9526	0.9430	0.9478	0.9433

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu121
Datasets 2.16.0
Tokenizers 0.15.0

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Dec 25, 2023
Updated: Dec 26, 2023