bert-finetuned-unpunctual-text-segmentation-v2

TankuVie/bert-finetuned-unpunctual-text-segmentation-v2

bert-finetuned-unpunctual-text-segmentation-v2 is a token classification model from TankuVie. 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: Jun 16, 2023
Updated: Jun 16, 2023
SHA: f16fc30b

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Model card

From the Hugging Face model README

bert-finetuned-unpunctual-text-segmentation-v2

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

Loss: 0.0010
Precision: 0.9989
Recall: 0.9979
F1: 0.9984
Accuracy: 0.9997

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0047	1.0	4750	0.0041	0.9892	0.9966	0.9929	0.9988
0.0015	2.0	9500	0.0017	0.9983	0.9953	0.9968	0.9995
0.0004	3.0	14250	0.0010	0.9989	0.9979	0.9984	0.9997

Framework versions

Transformers 4.31.0.dev0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Jun 16, 2023
Updated: Jun 16, 2023