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bert-base-german-cased-finetuned-subj_v6_7Epoch_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: 0.2860
- Precision: 0.7623
- Recall: 0.7514
- F1: 0.7568
- Accuracy: 0.9061
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: 7
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 33 | 0.3344 | 0.6846 | 0.5829 | 0.6296 | 0.8635 |
No log | 2.0 | 66 | 0.2659 | 0.7335 | 0.7 | 0.7164 | 0.8929 |
No log | 3.0 | 99 | 0.2490 | 0.7493 | 0.7514 | 0.7504 | 0.9090 |
No log | 4.0 | 132 | 0.2470 | 0.7676 | 0.7457 | 0.7565 | 0.9067 |
No log | 5.0 | 165 | 0.2669 | 0.7514 | 0.7514 | 0.7514 | 0.9044 |
No log | 6.0 | 198 | 0.2792 | 0.7564 | 0.7543 | 0.7554 | 0.9067 |
No log | 7.0 | 231 | 0.2860 | 0.7623 | 0.7514 | 0.7568 | 0.9061 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1