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bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.1
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: 0.0179
- Precision: 0.9249
- Recall: 0.8776
- F1: 0.9006
- Accuracy: 0.9942
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 |
---|---|---|---|---|---|---|---|
No log | 1.0 | 245 | 0.0244 | 0.9252 | 0.8120 | 0.8649 | 0.9924 |
No log | 2.0 | 490 | 0.0179 | 0.9249 | 0.8776 | 0.9006 | 0.9942 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1