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: 1.0503
• Accuracy: {'accuracy': 0.888}

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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.5703	{'accuracy': 0.841}
0.416	2.0	500	0.3604	{'accuracy': 0.889}
0.416	3.0	750	0.6394	{'accuracy': 0.884}
0.1901	4.0	1000	0.7093	{'accuracy': 0.885}
0.1901	5.0	1250	0.7750	{'accuracy': 0.885}
0.044	6.0	1500	0.9100	{'accuracy': 0.888}
0.044	7.0	1750	1.0710	{'accuracy': 0.887}
0.0151	8.0	2000	1.0063	{'accuracy': 0.888}
0.0151	9.0	2250	1.0483	{'accuracy': 0.892}
0.0107	10.0	2500	1.0503	{'accuracy': 0.888}

Framework versions

• PEFT 0.18.1
• Transformers 4.57.6
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.2