bert-finetuned-ner.default_parameters

Mabel465/bert-finetuned-ner.default_parameters

bert-finetuned-ner.default_parameters is a token classification model from Mabel465. 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: Nov 2, 2023
Updated: Nov 2, 2023
SHA: d0d435bf

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Base models

Model card

From the Hugging Face model README

bert-finetuned-ner.default_parameters

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2075
Precision: 0.5645
Recall: 0.4450
F1: 0.4977
Accuracy: 0.9228

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: 5e-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: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	425	0.1828	0.5952	0.3553	0.4449	0.9136
0.1165	2.0	850	0.1917	0.5760	0.4127	0.4808	0.9181
0.0438	3.0	1275	0.2075	0.5645	0.4450	0.4977	0.9228

Framework versions

Transformers 4.34.1
Pytorch 2.1.0
Datasets 2.14.6
Tokenizers 0.14.1

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Nov 2, 2023
Updated: Nov 2, 2023