bert-base-combined-large

This model is a fine-tuned version of dbmdz/bert-base-turkish-uncased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3029
  • Accuracy: 0.8940
  • F1: 0.8956

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: 32
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.2668 1.0 3077 0.2812 0.8931 0.8915
0.2042 2.0 6154 0.2675 0.8952 0.8950
0.1453 3.0 9231 0.3029 0.8940 0.8956

Framework versions

  • Transformers 4.21.2
  • Pytorch 1.12.1+cu102
  • Datasets 2.4.0
  • Tokenizers 0.12.1
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