distilbert_yelp_model

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

• Loss: 0.7957

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Yelp review full dataset (limited to 100,000 rows for efficiency)

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
0.9163	0.32	2000	0.9439
0.8424	0.64	4000	0.8211
0.8142	0.96	6000	0.8068
0.669	1.28	8000	0.8205
0.662	1.6	10000	0.7917
0.6364	1.92	12000	0.7957

Framework versions

• Transformers 4.48.3
• Pytorch 2.6.0+cu124
• Datasets 3.4.0
• Tokenizers 0.21.0