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: 2.6098
• Accuracy: {'accuracy': 0.37777777777777777}

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	405	2.0008	{'accuracy': 0.37037037037037035}
2.0177	2.0	810	2.0349	{'accuracy': 0.3802469135802469}
1.8336	3.0	1215	2.0526	{'accuracy': 0.35802469135802467}
1.7547	4.0	1620	2.1418	{'accuracy': 0.33827160493827163}
1.5832	5.0	2025	2.2398	{'accuracy': 0.36790123456790125}
1.5832	6.0	2430	2.2712	{'accuracy': 0.34814814814814815}
1.4297	7.0	2835	2.3660	{'accuracy': 0.3530864197530864}
1.2579	8.0	3240	2.4898	{'accuracy': 0.36790123456790125}
1.1612	9.0	3645	2.5870	{'accuracy': 0.35802469135802467}
0.9591	10.0	4050	2.6098	{'accuracy': 0.37777777777777777}

Framework versions

• PEFT 0.10.0
• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2