german_tc_professions_debates
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: 0.0487
- Precision: 0.9439
- Recall: 0.9739
- F1: 0.9587
- Accuracy: 0.9907
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: 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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 31 | 0.0423 | 0.9383 | 0.9646 | 0.9512 | 0.9894 |
No log | 2.0 | 62 | 0.0513 | 0.9017 | 0.9757 | 0.9373 | 0.9883 |
No log | 3.0 | 93 | 0.0444 | 0.9355 | 0.9739 | 0.9543 | 0.9902 |
No log | 4.0 | 124 | 0.0474 | 0.9457 | 0.9739 | 0.9596 | 0.9909 |
No log | 5.0 | 155 | 0.0487 | 0.9439 | 0.9739 | 0.9587 | 0.9907 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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