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: 1.2701
• Accuracy: {'accuracy': 0.867}

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	0.4135	{'accuracy': 0.854}
0.4732	2.0	500	0.5962	{'accuracy': 0.846}
0.4732	3.0	750	0.6645	{'accuracy': 0.869}
0.3296	4.0	1000	0.8788	{'accuracy': 0.86}
0.3296	5.0	1250	0.9247	{'accuracy': 0.858}
0.1992	6.0	1500	0.9763	{'accuracy': 0.871}
0.1992	7.0	1750	1.1154	{'accuracy': 0.866}
0.0876	8.0	2000	1.2105	{'accuracy': 0.87}
0.0876	9.0	2250	1.2144	{'accuracy': 0.871}
0.0436	10.0	2500	1.2701	{'accuracy': 0.867}

Framework versions

• PEFT 0.11.1
• Transformers 4.41.2
• Pytorch 2.3.0+cpu
• Datasets 2.16.0
• Tokenizers 0.19.1