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: 1.0415
• Accuracy: {'accuracy': 0.9}

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	0.4205	{'accuracy': 0.875}
0.4414	2.0	500	0.4863	{'accuracy': 0.868}
0.4414	3.0	750	0.5868	{'accuracy': 0.893}
0.1924	4.0	1000	0.6808	{'accuracy': 0.894}
0.1924	5.0	1250	0.7949	{'accuracy': 0.901}
0.0713	6.0	1500	0.8349	{'accuracy': 0.888}
0.0713	7.0	1750	0.9662	{'accuracy': 0.893}
0.0223	8.0	2000	0.9994	{'accuracy': 0.896}
0.0223	9.0	2250	1.0344	{'accuracy': 0.9}
0.008	10.0	2500	1.0415	{'accuracy': 0.9}

Framework versions

• PEFT 0.12.0
• Transformers 4.44.2
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1