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: 0.7678
• Accuracy: {'accuracy': 0.895}

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	0.2777	{'accuracy': 0.88}
No log	2.0	250	0.4062	{'accuracy': 0.872}
No log	3.0	375	0.4406	{'accuracy': 0.891}
0.2605	4.0	500	0.4675	{'accuracy': 0.898}
0.2605	5.0	625	0.6199	{'accuracy': 0.89}
0.2605	6.0	750	0.6202	{'accuracy': 0.897}
0.2605	7.0	875	0.7120	{'accuracy': 0.888}
0.0386	8.0	1000	0.7659	{'accuracy': 0.89}
0.0386	9.0	1125	0.7548	{'accuracy': 0.895}
0.0386	10.0	1250	0.7678	{'accuracy': 0.895}

Framework versions

• PEFT 0.11.1
• Transformers 4.39.3
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.2