moe_False_addTokens_True_clipLoss_True_cv_0

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

• Loss: 2.6310
• Model Preparation Time: 0.002
• F1: 0.1835
• Precision: 0.101
• Recall: 1.0
• Threshold: 0.8010
• Sim Ratio: 0.9796
• Pos Sim: 0.891
• Neg Sim: 0.9096

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: 0.0001
• 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: 1

Training results

Framework versions

• Transformers 4.47.1
• Pytorch 2.6.0+cu124
• Datasets 3.2.0
• Tokenizers 0.21.0