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: 1.0087
• Accuracy: {'accuracy': 0.886}

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	0.3263	{'accuracy': 0.882}
0.4298	2.0	500	0.4513	{'accuracy': 0.871}
0.4298	3.0	750	0.6971	{'accuracy': 0.864}
0.2176	4.0	1000	0.6914	{'accuracy': 0.877}
0.2176	5.0	1250	0.7609	{'accuracy': 0.889}
0.095	6.0	1500	0.8447	{'accuracy': 0.894}
0.095	7.0	1750	0.9361	{'accuracy': 0.888}
0.024	8.0	2000	0.9976	{'accuracy': 0.893}
0.024	9.0	2250	1.0071	{'accuracy': 0.885}
0.0097	10.0	2500	1.0087	{'accuracy': 0.886}

Framework versions

• Transformers 4.34.1
• Pytorch 1.13.0+cu117
• Datasets 2.14.6
• Tokenizers 0.14.1