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wvangils/
NL_BERT_michelin_finetuned

Name: NL_BERT_michelin_finetuned
Availability: InStock

generated_from_trainer

cmotions/NL_restaurant_reviews

autotrain_compatible

endpoints_compatible

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NL_BERT_michelin_finetuned

This model is a fine-tuned version of GroNLP/bert-base-dutch-cased on a Dutch restaurant reviews dataset. Provide Dutch review text to the API on the right and receive a score that indicates whether this restaurant is eligible for a Michelin star ;) It achieves the following results on the evaluation set:

Loss: 0.0637
Accuracy: 0.9836
Recall: 0.5486
Precision: 0.7914
F1: 0.6480
Mse: 0.0164

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: 32
eval_batch_size: 128
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	Accuracy	Recall	Precision	F1	Mse
0.1043	1.0	3647	0.0961	0.9792	0.3566	0.7606	0.4856	0.0208
0.0799	2.0	7294	0.0797	0.9803	0.4364	0.7415	0.5495	0.0197
0.0589	3.0	10941	0.0637	0.9836	0.5486	0.7914	0.6480	0.0164

Framework versions

Transformers 4.18.0
Pytorch 1.11.0+cu113
Datasets 2.1.0
Tokenizers 0.12.1

wvangils/NL_BERT_michelin_finetuned

NL_BERT_michelin_finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

wvangils/
NL_BERT_michelin_finetuned