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danskbert_indirect_speech

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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: 0.6577
  • Precision: 0.6982
  • Recall: 0.6577
  • F1: 0.6486
  • Loss: 0.8890

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 13 0.5310 0.2819 0.5310 0.3683 1.1024
No log 2.0 26 0.5329 0.5102 0.5329 0.3785 0.9938
No log 3.0 39 0.4206 0.5351 0.4206 0.2658 1.1366
No log 4.0 52 0.6118 0.6521 0.6118 0.5410 0.8100
No log 5.0 65 0.6691 0.6700 0.6691 0.6430 0.7886
No log 6.0 78 0.6214 0.6756 0.6214 0.5529 0.8290
No log 7.0 91 0.6182 0.7008 0.6182 0.5988 0.9558
No log 8.0 104 0.4476 0.7400 0.4476 0.3122 1.3500
No log 9.0 117 0.5997 0.7008 0.5997 0.5757 1.0460
No log 10.0 130 0.5717 0.7244 0.5717 0.5303 1.0733
No log 11.0 143 0.6566 0.7000 0.6566 0.6473 0.8322
No log 12.0 156 0.6562 0.7050 0.6562 0.6488 0.8855
No log 13.0 169 0.6711 0.6900 0.6711 0.6647 0.8431
No log 14.0 182 0.6208 0.7001 0.6208 0.6025 0.9622
No log 15.0 195 0.6823 0.7000 0.6823 0.6758 0.7811
No log 16.0 208 0.6611 0.6971 0.6611 0.6533 0.8808
No log 17.0 221 0.6677 0.6960 0.6677 0.6604 0.8277
No log 18.0 234 0.6579 0.6991 0.6579 0.6488 0.8897
No log 18.48 240 0.6577 0.6982 0.6577 0.6486 0.8890

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu124
  • Tokenizers 0.21.0