distilbert-base-uncased-pii-200

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

• Loss: 1.4704
• Overall Precision: 0.0
• Overall Recall: 0.0
• Overall F1: 0.0
• Overall Accuracy: 0.8065
• Email F1: 0.0
• Lastname F1: 0.0
• Prefix F1: 0.0

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: 5e-05
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.2
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Overall Precision	Overall Recall	Overall F1	Overall Accuracy	City F1	Email F1	Jobtype F1	Lastname F1	Prefix F1	Username F1
No log	1.0	1	2.5786	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0
No log	2.0	2	2.3959	0.0	0.0	0.0	0.1774	0.0	0.0	0.0	0.0	0.0	0.0
No log	3.0	3	2.0696	0.0	0.0	0.0	0.8065	0.0	0.0	0.0
No log	4.0	4	1.8231	0.0	0.0	0.0	0.8065	0.0	0.0	0.0
No log	5.0	5	1.6430	0.0	0.0	0.0	0.8065	0.0	0.0	0.0
No log	6.0	6	1.5266	0.0	0.0	0.0	0.8065	0.0	0.0	0.0
No log	7.0	7	1.4704	0.0	0.0	0.0	0.8065	0.0	0.0	0.0

Framework versions

• Transformers 4.42.4
• Pytorch 2.3.1+cu121
• Datasets 2.20.0
• Tokenizers 0.19.1