prompt-tackler_modernbert

This model is a fine-tuned version of jhu-clsp/mmBERT-small on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0119
• Accuracy: 0.9976
• Precision: 0.9976
• Recall: 0.9976
• F1: 0.9976

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• 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: 6
• mixed_precision_training: Native AMP

Training results

Framework versions

• Transformers 4.53.3
• Pytorch 2.9.1+cu128
• Datasets 2.21.0
• Tokenizers 0.21.4