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: 1.0072
• 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	0.3560	{'accuracy': 0.888}
0.4316	2.0	500	0.5124	{'accuracy': 0.878}
0.4316	3.0	750	0.6530	{'accuracy': 0.87}
0.2331	4.0	1000	0.6871	{'accuracy': 0.878}
0.2331	5.0	1250	0.8012	{'accuracy': 0.869}
0.0918	6.0	1500	0.8738	{'accuracy': 0.878}
0.0918	7.0	1750	0.8714	{'accuracy': 0.881}
0.0349	8.0	2000	0.9631	{'accuracy': 0.88}
0.0349	9.0	2250	1.0067	{'accuracy': 0.879}
0.0071	10.0	2500	1.0072	{'accuracy': 0.88}

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu121
• Datasets 2.16.1
• Tokenizers 0.15.1