RiskClassificationModel_20260217_071913_dedc7220

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: 1.3130
• Micro F1: 0.1047
• Macro F1: 0.0544
• Weighted F1: 0.1236
• Accuracy: 0.0
• Roc Auc: nan

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: 8
• eval_batch_size: 8
• 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: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Micro F1	Macro F1	Weighted F1	Accuracy	Roc Auc
1.2123	0.5682	50	1.3130	0.1047	0.0544	0.1236	0.0	nan

Framework versions

• Transformers 4.57.6
• Pytorch 2.6.0+cu124
• Datasets 4.4.2
• Tokenizers 0.22.1