distilbert-finetuned-mit-restaurant-ner – AI Model by naufalso | AlphaNeural AI

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naufalso/
distilbert-finetuned-mit-restaurant-ner

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-finetuned-mit-restaurant-ner

This model is a fine-tuned version of distilbert-base-uncased on the mit_restaurant dataset. It achieves the following results on the evaluation set:

Loss: 0.3210
Precision: 0.7768
Recall: 0.7983
F1: 0.7874
Accuracy: 0.9116

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	Precision	Recall	F1	Accuracy
0.6991	1.0	863	0.3478	0.7113	0.7684	0.7387	0.8994
0.2773	2.0	1726	0.3264	0.7533	0.7989	0.7754	0.9063
0.2164	3.0	2589	0.3137	0.7644	0.8045	0.7839	0.9121
0.1789	4.0	3452	0.3163	0.7755	0.7983	0.7867	0.9115
0.1573	5.0	4315	0.3210	0.7768	0.7983	0.7874	0.9116

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2