classifier-de / README.md
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MercuraTech/reranker-de-50k-classifier
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metadata
library_name: transformers
license: mit
base_model: bert-base-german-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - precision
  - recall
  - f1
model-index:
  - name: classifier-de
    results: []

classifier-de

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

  • Loss: 0.3460
  • Accuracy: 0.8811
  • Precision: 0.5353
  • Recall: 0.2849
  • F1: 0.3719

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: 1.5e-05
  • train_batch_size: 256
  • eval_batch_size: 256
  • 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
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Accuracy Precision Recall F1
0.2897 0.2569 500 0.3390 0.8773 0.5747 0.0282 0.0537
0.2437 0.5139 1000 0.3320 0.8789 0.5347 0.1568 0.2425
0.2292 0.7708 1500 0.3317 0.8826 0.5760 0.1901 0.2859
0.1915 1.0277 2000 0.3557 0.8820 0.5583 0.2164 0.3119
0.2146 1.2847 2500 0.3390 0.8837 0.5757 0.2250 0.3236
0.2222 1.5416 3000 0.3298 0.8811 0.5358 0.2819 0.3694
0.1861 1.7986 3500 0.3338 0.8823 0.5501 0.2620 0.3549
0.1789 2.0555 4000 0.3460 0.8811 0.5353 0.2849 0.3719
0.1739 2.3124 4500 0.3614 0.8850 0.5863 0.2368 0.3373
0.1899 2.5694 5000 0.3487 0.8844 0.5716 0.2578 0.3554
0.1692 2.8263 5500 0.3484 0.8847 0.5728 0.2653 0.3626

Framework versions

  • Transformers 4.51.3
  • Pytorch 2.7.0+cu126
  • Datasets 3.5.0
  • Tokenizers 0.21.1