distilbert-base-german-cased-finetuned-tagesschau-subcategories
This model is a fine-tuned version of distilbert-base-german-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5230
- Accuracy: 0.8267
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: 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 | Accuracy |
|---|---|---|---|---|
| No log | 0.4 | 30 | 1.5130 | 0.5733 |
| No log | 0.8 | 60 | 1.0629 | 0.7133 |
| No log | 1.2 | 90 | 0.8431 | 0.76 |
| No log | 1.6 | 120 | 0.7812 | 0.7467 |
| No log | 2.0 | 150 | 0.6373 | 0.78 |
| No log | 2.4 | 180 | 0.5567 | 0.8133 |
| No log | 2.8 | 210 | 0.5650 | 0.8067 |
| No log | 3.2 | 240 | 0.5068 | 0.8267 |
| No log | 3.6 | 270 | 0.5230 | 0.8267 |
| No log | 4.0 | 300 | 0.5318 | 0.8133 |
| No log | 4.4 | 330 | 0.5327 | 0.8067 |
| No log | 4.8 | 360 | 0.4918 | 0.82 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2