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: 1.0886
• Accuracy: {'accuracy': 0.877}

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	250	0.4107	{'accuracy': 0.89}
0.4454	2.0	500	0.4281	{'accuracy': 0.878}
0.4454	3.0	750	0.7015	{'accuracy': 0.874}
0.1947	4.0	1000	0.7794	{'accuracy': 0.876}
0.1947	5.0	1250	0.9013	{'accuracy': 0.874}
0.0711	6.0	1500	0.8924	{'accuracy': 0.88}
0.0711	7.0	1750	0.9679	{'accuracy': 0.881}
0.018	8.0	2000	1.0589	{'accuracy': 0.881}
0.018	9.0	2250	1.0792	{'accuracy': 0.886}
0.0036	10.0	2500	1.0886	{'accuracy': 0.877}

Framework versions

• PEFT 0.15.2
• Transformers 4.52.4
• Pytorch 2.6.0+cu124
• Datasets 3.6.0
• Tokenizers 0.21.1