bert-finetuned-ner

Brizape/bert-finetuned-ner

bert-finetuned-ner is a token classification model from Brizape. 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: Dec 5, 2022
Updated: Feb 22, 2023
SHA: fd5b6e93

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Model card

From the Hugging Face model README

bert-finetuned-ner

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

Loss: 0.2734
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.9388

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	34	0.3396	0.9388
No log	2.0	68	0.3204	0.9388
No log	3.0	102	0.2837	0.9388
No log	4.0	136	0.2751	0.9388
No log	5.0	170	0.2734	0.9388

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.0
Tokenizers 0.13.2

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Dec 5, 2022
Updated: Feb 22, 2023