DerivedFunction / lang-ner-xlmr

huggingface.co
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Model's Last Updated: April 10 2026
token-classification

Introduction of lang-ner-xlmr

Model Details of lang-ner-xlmr

lang-ner-xlmr

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

  • Loss: 0.0154
  • Precision: 0.9650
  • Recall: 0.9689
  • F1: 0.9669
  • Accuracy: 0.9959
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: 5e-05
  • train_batch_size: 128
  • eval_batch_size: 64
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 256
  • 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: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP
Training results
Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.0504 0.7111 5000 0.0214 0.9455 0.9556 0.9505 0.9942
0.0362 1.4221 10000 0.0178 0.9583 0.9628 0.9605 0.9951
0.0247 2.1331 15000 0.0166 0.9625 0.9673 0.9649 0.9956
0.0243 2.8442 20000 0.0154 0.9650 0.9689 0.9669 0.9959
Framework versions
  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.0.0
  • Tokenizers 0.22.2

Runs of DerivedFunction lang-ner-xlmr on huggingface.co

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lang-ner-xlmr install

lang-ner-xlmr is an open source model from GitHub that offers a free installation service, and any user can find lang-ner-xlmr on GitHub to install. At the same time, huggingface.co provides the effect of lang-ner-xlmr install, users can directly use lang-ner-xlmr installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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