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: 0.7392
• Accuracy: {'accuracy': 0.901}

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: 8
• eval_batch_size: 8
• 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	125	0.2589	{'accuracy': 0.896}
No log	2.0	250	0.4331	{'accuracy': 0.868}
No log	3.0	375	0.3884	{'accuracy': 0.901}
0.2587	4.0	500	0.4673	{'accuracy': 0.895}
0.2587	5.0	625	0.6184	{'accuracy': 0.899}
0.2587	6.0	750	0.6478	{'accuracy': 0.902}
0.2587	7.0	875	0.7249	{'accuracy': 0.899}
0.0338	8.0	1000	0.7446	{'accuracy': 0.893}
0.0338	9.0	1125	0.7290	{'accuracy': 0.9}
0.0338	10.0	1250	0.7392	{'accuracy': 0.901}

Framework versions

• PEFT 0.10.0
• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1