metadata
license: mit
base_model: deepset/gbert-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FragZONFactMetaRecommendation
results: []
widget:
- text: Wer arbeitet im Ressort PWG von ZEIT ONLINE?
example_title: Meta
- text: Wann ist Helmut Schmidt gestorben?
example_title: Fakt
- text: Was kann die ZEIT-KI?
example_title: Meta
- text: Wer hat 2021/22 die Meisterschaft der Fussballbundesliga gewonnen?
example_title: Fakt
- text: Wen soll ich bei der nächsten Bundestagswahl wählen?
example_title: Empfehlung
FragZONFactMetaRecommendation
This model is a fine-tuned version of deepset/gbert-large on the beta dataset. It achieves the following results on the evaluation set:
- Loss: 0.4128
- Accuracy: 0.9205
Model description
Fine-tuned gbert on queries
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.171 | 1.0 | 76 | 0.4003 | 0.9139 |
| 0.1154 | 2.0 | 152 | 0.4128 | 0.9205 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1