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: 0.9743
• Accuracy: {'accuracy': 0.89}

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	0.5011	{'accuracy': 0.849}
0.4507	2.0	500	0.3976	{'accuracy': 0.887}
0.4507	3.0	750	0.5992	{'accuracy': 0.891}
0.1928	4.0	1000	0.6172	{'accuracy': 0.897}
0.1928	5.0	1250	0.7082	{'accuracy': 0.89}
0.0827	6.0	1500	0.8177	{'accuracy': 0.89}
0.0827	7.0	1750	0.8743	{'accuracy': 0.886}
0.0127	8.0	2000	0.9673	{'accuracy': 0.892}
0.0127	9.0	2250	0.9793	{'accuracy': 0.89}
0.0103	10.0	2500	0.9743	{'accuracy': 0.89}

Framework versions

• PEFT 0.11.1
• Transformers 4.41.1
• Pytorch 2.3.0+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1