| --- |
| 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](https://huggingface.co/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 | |
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|
|
| ### Framework versions |
|
|
| - Transformers 4.34.0 |
| - Pytorch 2.0.1+cu118 |
| - Datasets 2.14.5 |
| - Tokenizers 0.14.1 |
|
|
