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metadata
library_name: transformers
license: cc-by-4.0
base_model: vesteinn/DanskBERT
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: danskbert_indirect_speech
    results: []

danskbert_indirect_speech

This model is a fine-tuned version of vesteinn/DanskBERT on an unknown dataset. It achieves the following results on the evaluation set:

  • Accuracy: 0.6698
  • Precision: 0.7042
  • Recall: 0.6698
  • F1: 0.6640
  • Loss: 0.7715

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 8
  • 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: 20
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Accuracy Precision Recall F1 Validation Loss
No log 1.0 9 0.3820 0.1459 0.3820 0.2112 1.1479
No log 2.0 18 0.3820 0.1459 0.3820 0.2112 1.4862
No log 3.0 27 0.5385 0.2900 0.5385 0.3770 1.0168
No log 4.0 36 0.3820 0.1459 0.3820 0.2112 1.0134
No log 5.0 45 0.4551 0.6492 0.4551 0.3461 0.9242
No log 6.0 54 0.6217 0.6269 0.6217 0.5716 0.7808
No log 7.0 63 0.6183 0.6601 0.6183 0.5446 0.7970
No log 8.0 72 0.4519 0.6933 0.4519 0.3345 1.0565
No log 9.0 81 0.7000 0.6985 0.7000 0.6842 0.7125
No log 10.0 90 0.6480 0.6978 0.6480 0.6395 0.7874
No log 11.0 99 0.6226 0.7064 0.6226 0.6062 0.8571
No log 12.0 108 0.5364 0.7104 0.5364 0.4812 1.1975
No log 13.0 117 0.7423 0.7327 0.7423 0.7336 0.6509
No log 14.0 126 0.7372 0.7275 0.7372 0.7306 0.6489
No log 15.0 135 0.5954 0.7039 0.5954 0.5712 0.9821
No log 16.0 144 0.7372 0.7317 0.7372 0.7258 0.6768
No log 17.0 153 0.6457 0.7049 0.6457 0.6355 0.8276
No log 17.8235 160 0.6698 0.7042 0.6698 0.6640 0.7715

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Tokenizers 0.21.0