pulf-classifier

This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0233
• Accuracy: 0.9943
• F1-score: 0.9887
• Recall: 0.9910
• Precision: 0.9863

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: 2e-05
• 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1-score	Recall	Precision
0.0243	1.0	8772	0.0228	0.9930	0.9861	0.9877	0.9846
0.0183	2.0	17544	0.0243	0.9937	0.9875	0.9927	0.9825
0.0124	3.0	26316	0.0233	0.9943	0.9887	0.9910	0.9863

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3