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: 1.0684
• Accuracy: {'accuracy': 0.879}

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	0.4266	{'accuracy': 0.87}
0.4232	2.0	500	0.4260	{'accuracy': 0.88}
0.4232	3.0	750	0.5071	{'accuracy': 0.885}
0.2213	4.0	1000	0.7424	{'accuracy': 0.875}
0.2213	5.0	1250	0.7885	{'accuracy': 0.881}
0.067	6.0	1500	0.9312	{'accuracy': 0.872}
0.067	7.0	1750	0.9669	{'accuracy': 0.874}
0.0238	8.0	2000	1.0856	{'accuracy': 0.874}
0.0238	9.0	2250	1.0637	{'accuracy': 0.88}
0.0066	10.0	2500	1.0684	{'accuracy': 0.879}

Framework versions

• Transformers 4.32.1
• Pytorch 2.0.1
• Datasets 2.14.4
• Tokenizers 0.13.2