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: 0.7723
• Accuracy: {'accuracy': 0.85}

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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	25	0.6017	{'accuracy': 0.66}
No log	2.0	50	0.3176	{'accuracy': 0.88}
No log	3.0	75	0.5090	{'accuracy': 0.86}
No log	4.0	100	0.5618	{'accuracy': 0.89}
No log	5.0	125	0.6232	{'accuracy': 0.86}
No log	6.0	150	0.6672	{'accuracy': 0.86}
No log	7.0	175	0.7276	{'accuracy': 0.86}
No log	8.0	200	0.7465	{'accuracy': 0.86}
No log	9.0	225	0.7828	{'accuracy': 0.85}
No log	10.0	250	0.7723	{'accuracy': 0.85}

Framework versions

• PEFT 0.13.2
• Transformers 4.46.2
• Pytorch 2.5.1+cu121
• Datasets 3.1.0
• Tokenizers 0.20.3