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distilbert-base-multilingual-cased-finetuned-ner

This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on the conllpp dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0632
  • Precision: 0.9282
  • Recall: 0.9340
  • F1: 0.9311
  • Accuracy: 0.9839

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Precision Recall F1 Accuracy
0.237 1.0 878 0.0732 0.9083 0.9188 0.9135 0.9794
0.0533 2.0 1756 0.0648 0.9265 0.9274 0.9269 0.9827
0.0303 3.0 2634 0.0632 0.9282 0.9340 0.9311 0.9839

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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Dataset used to train janko/distilbert-base-multilingual-cased-finetuned-ner

Evaluation results