finetuned_model_sentiment_analysis_yelp

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

• Loss: 0.8933
• Precision: 0.6404
• Recall: 0.6409
• F1: 0.6405

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1
0.8691	1.0	3657	0.8801	0.6224	0.6201	0.6149
0.7506	2.0	7314	0.8469	0.6458	0.6421	0.6428
0.6087	3.0	10971	0.8933	0.6404	0.6409	0.6405

Framework versions

• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2