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Klassifizierung-Gewerke
Simon17/Klassifizierung-Gewerke
Klassifizierung-Gewerke is a text classification model from Simon17. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
This model is a fine-tuned version of bert-base-german-cased on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0398 - F1: 0.9931
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Sep 29, 2022
- Updated
- Oct 13, 2022
- SHA
- a3dddedf
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Model card
From the Hugging Face model README
Klassifizierung-Gewerke
This model is a fine-tuned version of bert-base-german-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0398
- F1: 0.9931
Model description
The model is based on a BACnet data set and makes it possible to classify them according to trades.
Intended uses & limitations
More information needed
Training and evaluation data
The model is based on a German-based language dataset.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.1473 | 1.0 | 726 | 0.0952 | 0.9822 |
| 0.0252 | 2.0 | 1452 | 0.0488 | 0.9918 |
| 0.028 | 3.0 | 2178 | 0.0398 | 0.9931 |
Framework versions
- Transformers 4.22.2
- Pytorch 1.12.1+cu113
- Datasets 2.5.1
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Sep 29, 2022
- Updated
- Oct 13, 2022