ner_bert_model

DipakBundheliya/ner_bert_model

ner_bert_model is a token classification model from DipakBundheliya. 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: bert
Access: Public
Created: Mar 28, 2024
Updated: Mar 28, 2024
SHA: be6986f8

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Base models

Datasets

shipping_label_ner

Model card

From the Hugging Face model README

ner_bert_model

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

Loss: 0.4145
Precision: 0.8235
Recall: 0.9333
F1: 0.8750
Accuracy: 0.9096

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: 8
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	7	1.7796	0.0	0.0	0.0	0.4294
No log	2.0	14	1.4530	0.5	0.2667	0.3478	0.5650
No log	3.0	21	1.1854	0.5510	0.36	0.4355	0.6384
No log	4.0	28	0.9850	0.6667	0.5867	0.6241	0.7345
No log	5.0	35	0.8189	0.6622	0.6533	0.6577	0.7797
No log	6.0	42	0.7194	0.6914	0.7467	0.7179	0.8192
No log	7.0	49	0.6126	0.7262	0.8133	0.7673	0.8588
No log	8.0	56	0.5760	0.75	0.88	0.8098	0.8701
No log	9.0	63	0.4819	0.8	0.9067	0.8500	0.8927
No log	10.0	70	0.4610	0.7907	0.9067	0.8447	0.8983
No log	11.0	77	0.4471	0.8	0.9067	0.8500	0.8927
No log	12.0	84	0.4203	0.7931	0.92	0.8519	0.9040
No log	13.0	91	0.4281	0.8256	0.9467	0.8820	0.9153
No log	14.0	98	0.3913	0.8256	0.9467	0.8820	0.9153
No log	15.0	105	0.3966	0.8235	0.9333	0.8750	0.9096
No log	16.0	112	0.4033	0.8235	0.9333	0.8750	0.9096
No log	17.0	119	0.4149	0.8140	0.9333	0.8696	0.9040
No log	18.0	126	0.4150	0.8140	0.9333	0.8696	0.9040
No log	19.0	133	0.4122	0.8235	0.9333	0.8750	0.9096
No log	20.0	140	0.4145	0.8235	0.9333	0.8750	0.9096

Framework versions

Transformers 4.39.1
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 28, 2024
Updated: Mar 28, 2024