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gecco-bert-base-german-uncased

Text classification on German E-Counseling Conversations.

This model is a fine-tuned version of dbmdz/bert-base-german-uncased trained with the German E-Counseling Conversation Dataset, created at the Technische Hochschule Nürnberg (see github.com/th-nuernberg/gecco-dataset).

It achieves the following results on the evaluation set:

  • Loss: 1.2341
  • Accuracy: 0.6968
  • F1: 0.4493

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 16

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
3.4151 1.0 20 3.0885 0.2935 0.0760
2.9316 2.0 40 2.7003 0.3484 0.1035
2.5556 3.0 60 2.3463 0.5032 0.2350
2.19 4.0 80 2.0714 0.5613 0.2841
1.904 5.0 100 1.8381 0.6 0.3085
1.6285 6.0 120 1.6712 0.6323 0.3633
1.4482 7.0 140 1.5518 0.6581 0.3774
1.2807 8.0 160 1.4796 0.6677 0.3880
1.1126 9.0 180 1.4207 0.6613 0.3787
1.0747 10.0 200 1.3461 0.6774 0.3885
0.9068 11.0 220 1.3097 0.6871 0.4132
0.8498 12.0 240 1.2893 0.6903 0.4235
0.8343 13.0 260 1.2549 0.7 0.4332
0.7375 14.0 280 1.2426 0.7 0.4497
0.7274 15.0 300 1.2385 0.7 0.4512
0.6916 16.0 320 1.2341 0.6968 0.4493

Framework versions

  • Transformers 4.35.1
  • Pytorch 1.10.1+cu111
  • Datasets 2.14.7
  • Tokenizers 0.14.1
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