upvantage / modernbert-KK-groups3

huggingface.co
Total runs: 8
24-hour runs: 0
7-day runs: 0
30-day runs: 8
Model's Last Updated: September 05 2025
text-classification

Introduction of modernbert-KK-groups3

Model Details of modernbert-KK-groups3

modernbert-KK-groups3

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: 0.0405
  • Accuracy: 0.9863
  • F1: 0.9863
  • Precision: 0.9863
  • Recall: 0.9863
  • F1 Class 0: 0.9868
  • Precision Class 0: 0.9856
  • Recall Class 0: 0.9879
  • F1 Class 1: 0.9859
  • Precision Class 1: 0.9871
  • Recall Class 1: 0.9846
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: 600
  • eval_batch_size: 600
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 4800
  • total_eval_batch_size: 4800
  • 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
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
0.331 1.0 5911 0.0405 0.9863 0.9863 0.9863 0.9863 0.9868 0.9856 0.9879 0.9859 0.9871 0.9846
Framework versions
  • Transformers 4.56.1
  • Pytorch 2.8.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.0

Runs of upvantage modernbert-KK-groups3 on huggingface.co

8
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0
24-hour runs
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3-day runs
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7-day runs
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