--- tags: - generated_from_trainer metrics: - accuracy base_model: Mathking/bert-base-german-cased-gnad10 model-index: - name: bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories results: [] --- # bert-base-german-cased-gnad10-finetuned-tagesschau-subcategories This model is a fine-tuned version of [Mathking/bert-base-german-cased-gnad10](https://huggingface.co/Mathking/bert-base-german-cased-gnad10) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.4327 - Accuracy: 0.8733 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 1.3737 | 0.4 | 30 | 0.9333 | 0.7133 | | 0.7848 | 0.8 | 60 | 0.5591 | 0.8133 | | 0.4933 | 1.2 | 90 | 0.4939 | 0.8 | | 0.3441 | 1.6 | 120 | 0.5537 | 0.8133 | | 0.3972 | 2.0 | 150 | 0.4229 | 0.8533 | | 0.2103 | 2.4 | 180 | 0.4327 | 0.8733 | | 0.1783 | 2.8 | 210 | 0.4834 | 0.8467 | | 0.1367 | 3.2 | 240 | 0.4634 | 0.86 | | 0.1273 | 3.6 | 270 | 0.4828 | 0.8467 | ### Framework versions - Transformers 4.25.1 - Pytorch 1.12.1+cu113 - Datasets 2.7.1 - Tokenizers 0.13.2