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: 1.0878
• 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	0.3774	{'accuracy': 0.863}
0.3793	2.0	500	0.3980	{'accuracy': 0.884}
0.3793	3.0	750	0.6004	{'accuracy': 0.885}
0.1356	4.0	1000	0.7604	{'accuracy': 0.884}
0.1356	5.0	1250	0.8298	{'accuracy': 0.887}
0.0431	6.0	1500	0.9589	{'accuracy': 0.883}
0.0431	7.0	1750	1.0109	{'accuracy': 0.883}
0.0202	8.0	2000	1.0334	{'accuracy': 0.884}
0.0202	9.0	2250	1.0635	{'accuracy': 0.88}
0.0095	10.0	2500	1.0878	{'accuracy': 0.88}

Framework versions

• PEFT 0.13.0
• Transformers 4.44.2
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.19.1