distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.9748
• Accuracy: {'accuracy': 0.88}

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	0.3807	{'accuracy': 0.879}
0.4088	2.0	500	0.7833	{'accuracy': 0.838}
0.4088	3.0	750	0.6331	{'accuracy': 0.871}
0.2014	4.0	1000	0.6576	{'accuracy': 0.88}
0.2014	5.0	1250	0.7551	{'accuracy': 0.876}
0.0667	6.0	1500	0.8506	{'accuracy': 0.876}
0.0667	7.0	1750	0.8710	{'accuracy': 0.881}
0.0164	8.0	2000	0.9710	{'accuracy': 0.88}
0.0164	9.0	2250	0.9511	{'accuracy': 0.882}
0.0064	10.0	2500	0.9748	{'accuracy': 0.88}

Framework versions

• PEFT 0.10.0
• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2