germanic_peoplecentric_eng_bert

This model is a fine-tuned version of google-bert/bert-large-cased on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5801
  • Accuracy: 0.7368
  • F1: 0.7765

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 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 Accuracy F1
No log 1.0 76 0.6284 0.6316 0.7021
0.6378 2.0 152 0.5622 0.7204 0.7592
0.4262 3.0 228 0.5801 0.7368 0.7765

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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