metadata
language:
- ger
license: mit
base_model: deepset/gbert-large
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: th-nuernberg/gbert-large-german-counseling-gecco
results: []
th-nuernberg/gbert-large-german-counseling-gecco
This model is a fine-tuned version of deepset/gbert-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9290
- Accuracy: 0.7839
- F1: 0.6645
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