license	base_model	tags	metrics	model-index	widget	datasets
apache-2.0	distilbert-base-uncased	generated_from_trainer	accuracy f1 precision recall	name results DistilBERT-yelp-sentiment-analysis	text example_title This restaurant has the best food Positive review text example_title This restaurant has the worst food Negative review	noahnsimbe/yelp-dataset

DistilBERT-yelp-sentiment-analysis

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

• Loss: 0.2995
• Accuracy: 0.8930
• F1: 0.7863
• Precision: 0.7976
• Recall: 0.7768

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.2996	1.0	9645	0.2995	0.8930	0.7863	0.7976	0.7768
0.2233	2.0	19290	0.3381	0.8966	0.7957	0.8015	0.7907

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2