distilbert-base-uncased-lora-text-classification

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: 0.9528
• Accuracy: {'accuracy': 0.887}

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: 0.001
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.3796	{'accuracy': 0.88}
0.4157	2.0	500	0.4191	{'accuracy': 0.879}
0.4157	3.0	750	0.6114	{'accuracy': 0.867}
0.1906	4.0	1000	0.5635	{'accuracy': 0.882}
0.1906	5.0	1250	0.7240	{'accuracy': 0.879}
0.0727	6.0	1500	0.8097	{'accuracy': 0.883}
0.0727	7.0	1750	0.9097	{'accuracy': 0.888}
0.0275	8.0	2000	0.9154	{'accuracy': 0.887}
0.0275	9.0	2250	0.9432	{'accuracy': 0.886}
0.0133	10.0	2500	0.9528	{'accuracy': 0.887}

Framework versions

• PEFT 0.4.0
• Transformers 4.37.1
• Pytorch 2.1.2+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1