DistilBERT-finetuned-customer-queries

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: 0.1443
• Accuracy: 0.9935
• F1: 0.9935

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: 64
• eval_batch_size: 64
• 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
1.6111	1.0	250	0.3456	0.9895	0.9895
0.264	2.0	500	0.1443	0.9935	0.9935

Framework versions

• Transformers 4.42.1
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1