OR_finetuned_classification

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

• Loss: 0.6007
• F1: 0.6667
• Roc Auc: 0.8095
• Accuracy: 0.6667

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: 0.0002
• 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: 300

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.0016	79.0	790	0.4859	0.6667	0.8095	0.6667
0.0006	158.0	1580	0.5649	0.6667	0.8095	0.6667
0.0004	237.0	2370	0.6007	0.6667	0.8095	0.6667

Framework versions

• Transformers 4.45.2
• Pytorch 2.4.0+cu124
• Datasets 3.0.1
• Tokenizers 0.20.1