testThesisSmallSMP

Nonzerophilip/testThesisSmallSMP

testThesisSmallSMP is a token classification model from Nonzerophilip. Use it when you need labels on individual words, such as names. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
Model type: bert
Access: Public
Created: Sep 22, 2023
Updated: Sep 22, 2023
SHA: 74ecda31

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Base models

KBLab/bert-base-swedish-cased-ner

Model card

From the Hugging Face model README

testThesisSmallSMP

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

Loss: 0.3275
Precision: 0.6826
Recall: 0.6477
F1: 0.6647
Accuracy: 0.8940

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
No log	1.0	39	0.4518	0.4107	0.2614	0.3194	0.8555
No log	2.0	78	0.3469	0.6687	0.6193	0.6431	0.8923
No log	3.0	117	0.3275	0.6826	0.6477	0.6647	0.8940

Framework versions

Transformers 4.33.0
Pytorch 2.0.1
Datasets 2.14.5
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: bert
Created: Sep 22, 2023
Updated: Sep 22, 2023