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: 0.6932
• Accuracy: {'accuracy': 0.5}

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	0.6933	{'accuracy': 0.5}
0.7418	2.0	500	0.6956	{'accuracy': 0.5}
0.7418	3.0	750	0.7195	{'accuracy': 0.5}
0.7061	4.0	1000	0.7541	{'accuracy': 0.5}
0.7061	5.0	1250	0.6933	{'accuracy': 0.5}
0.6982	6.0	1500	0.6931	{'accuracy': 0.5}
0.6982	7.0	1750	0.6932	{'accuracy': 0.5}
0.6943	8.0	2000	0.6931	{'accuracy': 0.5}
0.6943	9.0	2250	0.6932	{'accuracy': 0.5}
0.6932	10.0	2500	0.6932	{'accuracy': 0.5}

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.0