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: 1.3394
• Accuracy: {'accuracy': 0.867}

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	0.5972	{'accuracy': 0.871}
0.3494	2.0	500	0.6138	{'accuracy': 0.867}
0.3494	3.0	750	0.8990	{'accuracy': 0.862}
0.176	4.0	1000	1.1045	{'accuracy': 0.865}
0.176	5.0	1250	1.1309	{'accuracy': 0.874}
0.0495	6.0	1500	1.1944	{'accuracy': 0.877}
0.0495	7.0	1750	1.3032	{'accuracy': 0.87}
0.0199	8.0	2000	1.2579	{'accuracy': 0.875}
0.0199	9.0	2250	1.2924	{'accuracy': 0.87}
0.0102	10.0	2500	1.3394	{'accuracy': 0.867}

Framework versions

• PEFT 0.17.1
• Transformers 4.57.1
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1