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: 0.6274
• Accuracy: {'accuracy': 0.898}

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 with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.5209	{'accuracy': 0.854}
0.4334	2.0	500	0.4871	{'accuracy': 0.871}
0.4334	3.0	750	0.4843	{'accuracy': 0.892}
0.1658	4.0	1000	0.6047	{'accuracy': 0.893}
0.1658	5.0	1250	0.6274	{'accuracy': 0.898}

Framework versions

• PEFT 0.14.0
• Transformers 4.50.2
• Pytorch 2.6.0+cu124
• Datasets 3.5.0
• Tokenizers 0.21.1