upvantage / modernbert-rewritten-512

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Total runs: 10
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7-day runs: 0
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Model's Last Updated: August 11 2025
text-classification

Introduction of modernbert-rewritten-512

Model Details of modernbert-rewritten-512

modernbert-rewritten-512

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: 0.0845
  • Accuracy: 0.9709
  • F1: 0.9709
  • Precision: 0.9711
  • Recall: 0.9709
  • F1 Class 0: 0.9717
  • Precision Class 0: 0.9630
  • Recall Class 0: 0.9805
  • F1 Class 1: 0.9701
  • Precision Class 1: 0.9794
  • Recall Class 1: 0.9610
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: 8
  • total_train_batch_size: 1024
  • total_eval_batch_size: 1024
  • 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
0.6368 1.0 819 0.0845 0.9709 0.9709 0.9711 0.9709 0.9717 0.9630 0.9805 0.9701 0.9794 0.9610
Framework versions
  • Transformers 4.55.0
  • Pytorch 2.8.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.21.4

Runs of upvantage modernbert-rewritten-512 on huggingface.co

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