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bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v2
This model is a fine-tuned version of bert-base-german-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0074
- Precision: 0.9776
- Recall: 0.9593
- F1: 0.9683
- Accuracy: 0.9981
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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.038 | 1.0 | 625 | 0.0091 | 0.9694 | 0.9426 | 0.9559 | 0.9974 |
| 0.0079 | 2.0 | 1250 | 0.0074 | 0.9776 | 0.9593 | 0.9683 | 0.9981 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
