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: 0.8136
• Accuracy: {'accuracy': 0.893}

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: 8
• eval_batch_size: 8
• 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	125	0.2775	{'accuracy': 0.887}
No log	2.0	250	0.4787	{'accuracy': 0.864}
No log	3.0	375	0.4367	{'accuracy': 0.887}
0.2436	4.0	500	0.5377	{'accuracy': 0.889}
0.2436	5.0	625	0.8811	{'accuracy': 0.874}
0.2436	6.0	750	0.7428	{'accuracy': 0.891}
0.2436	7.0	875	0.7456	{'accuracy': 0.883}
0.0283	8.0	1000	0.8222	{'accuracy': 0.893}
0.0283	9.0	1125	0.8001	{'accuracy': 0.892}
0.0283	10.0	1250	0.8136	{'accuracy': 0.893}

Framework versions

• PEFT 0.11.1
• Transformers 4.41.2
• Pytorch 2.3.1+cu121
• Datasets 2.19.2
• Tokenizers 0.19.1