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: 1.0105
• Accuracy: {'accuracy': 0.892}

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	0.5723	{'accuracy': 0.834}
0.4214	2.0	500	0.5061	{'accuracy': 0.873}
0.4214	3.0	750	0.6230	{'accuracy': 0.889}
0.1992	4.0	1000	0.7189	{'accuracy': 0.883}
0.1992	5.0	1250	0.9885	{'accuracy': 0.879}
0.066	6.0	1500	0.8311	{'accuracy': 0.884}
0.066	7.0	1750	0.8853	{'accuracy': 0.894}
0.0155	8.0	2000	0.9528	{'accuracy': 0.895}
0.0155	9.0	2250	0.9955	{'accuracy': 0.889}
0.0128	10.0	2500	1.0105	{'accuracy': 0.892}

Framework versions

• PEFT 0.9.0
• Transformers 4.38.2
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2