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: 0.9904
• Accuracy: {'accuracy': 0.899}

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	0.5709	{'accuracy': 0.837}
0.4386	2.0	500	0.4510	{'accuracy': 0.871}
0.4386	3.0	750	0.6571	{'accuracy': 0.887}
0.1891	4.0	1000	0.6197	{'accuracy': 0.894}
0.1891	5.0	1250	0.7688	{'accuracy': 0.897}
0.0683	6.0	1500	0.8231	{'accuracy': 0.892}
0.0683	7.0	1750	0.8949	{'accuracy': 0.901}
0.0136	8.0	2000	0.9553	{'accuracy': 0.896}
0.0136	9.0	2250	1.0202	{'accuracy': 0.892}
0.0067	10.0	2500	0.9904	{'accuracy': 0.899}

Framework versions

• PEFT 0.9.0
• Transformers 4.39.0.dev0
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.15.2