upvantage / modernbert-23m-typo

huggingface.co
Total runs: 7
24-hour runs: 0
7-day runs: 0
30-day runs: 7
Model's Last Updated: September 14 2025
text-classification

Introduction of modernbert-23m-typo

Model Details of modernbert-23m-typo

modernbert-23m-typo

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: 0.0283
  • Accuracy: 0.9898
  • F1: 0.9898
  • Precision: 0.9898
  • Recall: 0.9898
  • F1 Class 0: 0.9898
  • Precision Class 0: 0.9895
  • Recall Class 0: 0.9901
  • F1 Class 1: 0.9898
  • Precision Class 1: 0.9900
  • Recall Class 1: 0.9895
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: 7.9e-05
  • train_batch_size: 2000
  • eval_batch_size: 2000
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 16000
  • total_eval_batch_size: 16000
  • 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: 0.06
  • 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
0.2336 1.0 1436 0.0283 0.9898 0.9898 0.9898 0.9898 0.9898 0.9895 0.9901 0.9898 0.9900 0.9895
Framework versions
  • Transformers 4.56.1
  • Pytorch 2.8.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.0

Runs of upvantage modernbert-23m-typo on huggingface.co

7
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
7
30-day runs

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