This model is a fine-tuned version of molise-ai/pii-detector-ai4privacy on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.5005
Precision: 0.2146
Recall: 0.2053
F1: 0.2099
Accuracy: 0.8511

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: 3e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.533	1.0	5036	0.5103	0.1664	0.1261	0.1435	0.8251
0.458	2.0	10072	0.4788	0.1882	0.1479	0.1656	0.8366
0.3836	3.0	15108	0.4481	0.1953	0.1572	0.1742	0.8441
0.3576	4.0	20144	0.4498	0.1925	0.1657	0.1781	0.8439
0.3189	5.0	25180	0.4445	0.2039	0.1872	0.1952	0.8491
0.2837	6.0	30216	0.4631	0.2121	0.1956	0.2035	0.8499
0.2521	7.0	35252	0.4882	0.2144	0.2021	0.2081	0.8516
0.2303	8.0	40288	0.5005	0.2146	0.2053	0.2099	0.8511

Framework versions

Transformers 4.50.0
Pytorch 2.6.0+cu124
Datasets 3.4.1
Tokenizers 0.21.1

AndreaMaugeri71295/PII_classification_m2

PII_classification_m2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

AndreaMaugeri71295/
PII_classification_m2