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: 0.0000
• Accuracy: {'accuracy': 1.0}

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	171	0.0001	{'accuracy': 1.0}
No log	2.0	342	0.0001	{'accuracy': 1.0}
0.0245	3.0	513	0.0001	{'accuracy': 1.0}
0.0245	4.0	684	0.0000	{'accuracy': 1.0}
0.0245	5.0	855	0.0001	{'accuracy': 1.0}
0.0	6.0	1026	0.0000	{'accuracy': 1.0}
0.0	7.0	1197	0.0000	{'accuracy': 1.0}
0.0	8.0	1368	0.0000	{'accuracy': 1.0}
0.0	9.0	1539	0.0000	{'accuracy': 1.0}
0.0	10.0	1710	0.0000	{'accuracy': 1.0}

Framework versions

• PEFT 0.8.2
• Transformers 4.37.2
• Pytorch 2.1.0+cu121
• Datasets 2.17.1
• Tokenizers 0.15.2