turkish-ner-fold-bBERT5

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

  • Loss: 0.3151
  • F1: 0.6423
  • Precision: 0.6301
  • Recall: 0.6550
  • Accuracy: 0.9049

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: 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: 5

Training results

Training Loss Epoch Step Validation Loss F1 Precision Recall Accuracy
0.4095 1.0 500 0.3264 0.5578 0.5579 0.5577 0.8747
0.2751 2.0 1000 0.2901 0.6305 0.6227 0.6385 0.8927
0.2126 3.0 1500 0.2820 0.6337 0.6356 0.6318 0.8996
0.1636 4.0 2000 0.2948 0.6507 0.6514 0.6501 0.9038
0.1275 5.0 2500 0.3136 0.6524 0.6445 0.6604 0.9023

Framework versions

  • Transformers 4.48.3
  • Pytorch 2.5.1+cu124
  • Datasets 3.3.2
  • Tokenizers 0.21.0
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Dataset used to train meryemmm22/turkish-ner-fold-mBERT5

Evaluation results