modernbert-Aegis-Content-Safety-2.0

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

• Loss: 0.4780
• Accuracy: 0.8166
• F1: 0.8532

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: 0.003
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 3
• mixed_precision_training: Native AMP
• label_smoothing_factor: 0.1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.529	1.0	938	0.4920	0.8069	0.8498
0.5	2.0	1876	0.4850	0.8104	0.8553
0.4833	3.0	2814	0.4780	0.8166	0.8532

Framework versions

• Transformers 4.50.2
• Pytorch 2.6.0+cu126
• Datasets 3.3.1
• Tokenizers 0.21.0