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: 0.9692
• Accuracy: {'accuracy': 0.891}

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	0.3471	{'accuracy': 0.884}
0.4071	2.0	500	0.5222	{'accuracy': 0.869}
0.4071	3.0	750	0.5641	{'accuracy': 0.897}
0.1929	4.0	1000	0.5622	{'accuracy': 0.898}
0.1929	5.0	1250	0.8867	{'accuracy': 0.88}
0.0629	6.0	1500	0.8944	{'accuracy': 0.888}
0.0629	7.0	1750	0.8773	{'accuracy': 0.888}
0.0284	8.0	2000	0.9412	{'accuracy': 0.891}
0.0284	9.0	2250	0.9415	{'accuracy': 0.892}
0.0128	10.0	2500	0.9692	{'accuracy': 0.891}

Framework versions

• PEFT 0.12.0
• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1