th-nuernberg/gbert-large-german-counseling-gecco

This model is a fine-tuned version of deepset/gbert-large 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: Accuracy 0.78, F1 0.66.

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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
3.3924 1.0 20 2.9410 0.2032 0.0418
2.7028 2.0 40 2.2499 0.4806 0.2366
2.0665 3.0 60 1.7404 0.6129 0.3537
1.5 4.0 80 1.3602 0.6839 0.4109
1.0794 5.0 100 1.1377 0.7355 0.4971
0.7965 6.0 120 1.0123 0.7548 0.5518
0.6438 7.0 140 0.9806 0.7613 0.5547
0.5039 8.0 160 0.9452 0.7742 0.6019
0.4058 9.0 180 0.9218 0.7774 0.5907
0.3363 10.0 200 0.9373 0.7710 0.6157
0.2451 11.0 220 0.9751 0.7548 0.5955
0.1997 12.0 240 0.9197 0.7839 0.6526
0.1765 13.0 260 0.9187 0.7806 0.6425
0.1453 14.0 280 0.9431 0.7742 0.6357
0.1216 15.0 300 0.9388 0.7839 0.6534
0.1097 16.0 320 0.9290 0.7839 0.6645

Framework versions

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