bert-base-uncased-lora-text-classification

This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:

• Loss: 0.2267
• Accuracy: {'accuracy': 0.92824}
• F1: 0.9288

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.2608	1.0	1563	0.2187	{'accuracy': 0.91768}	0.9177
0.246	2.0	3126	0.2070	{'accuracy': 0.92096}	0.9205
0.2056	3.0	4689	0.2051	{'accuracy': 0.92572}	0.9259
0.1748	4.0	6252	0.2570	{'accuracy': 0.92288}	0.9249
0.1494	5.0	7815	0.2267	{'accuracy': 0.92824}	0.9288

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0