modern-5-20-pairs-200k-labeled

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

  • Loss: 0.0631
  • Accuracy: 0.9878
  • F1: 0.9878
  • Precision: 0.9878
  • Recall: 0.9878
  • F1 Class 0: 0.9879
  • Precision Class 0: 0.9909
  • Recall Class 0: 0.9849
  • F1 Class 1: 0.9877
  • Precision Class 1: 0.9846
  • Recall Class 1: 0.9908

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: 1e-05
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • total_train_batch_size: 512
  • total_eval_batch_size: 512
  • optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1
  • label_smoothing_factor: 0.01

Training results

Training Loss Epoch Step Validation Loss Accuracy F1 Precision Recall F1 Class 0 Precision Class 0 Recall Class 0 F1 Class 1 Precision Class 1 Recall Class 1
0.2445 1.0 588 0.0631 0.9878 0.9878 0.9878 0.9878 0.9879 0.9909 0.9849 0.9877 0.9846 0.9908

Framework versions

  • Transformers 4.55.2
  • Pytorch 2.8.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.21.4
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