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: 1.1367
• Accuracy: {'accuracy': 0.881}

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	0.5355	{'accuracy': 0.834}
0.4237	2.0	500	0.5577	{'accuracy': 0.867}
0.4237	3.0	750	0.7444	{'accuracy': 0.868}
0.1861	4.0	1000	0.6896	{'accuracy': 0.884}
0.1861	5.0	1250	0.9201	{'accuracy': 0.881}
0.0388	6.0	1500	0.9153	{'accuracy': 0.894}
0.0388	7.0	1750	1.1074	{'accuracy': 0.877}
0.0076	8.0	2000	1.0988	{'accuracy': 0.883}
0.0076	9.0	2250	1.1251	{'accuracy': 0.878}
0.0029	10.0	2500	1.1367	{'accuracy': 0.881}

Framework versions

• PEFT 0.10.0
• Transformers 4.40.2
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1