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bert-base-german-cased-noisy-pretrain-fine-tuned
This model is a fine-tuned version of tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2925
- Precision: 0.7933
- Recall: 0.7457
- F1: 0.7688
- Accuracy: 0.9147
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 | 0.3093 | 0.7456 | 0.6029 | 0.6667 | 0.8808 |
| No log | 2.0 | 66 | 0.2587 | 0.7774 | 0.7286 | 0.7522 | 0.9078 |
| No log | 3.0 | 99 | 0.2529 | 0.7775 | 0.7686 | 0.7730 | 0.9136 |
| No log | 4.0 | 132 | 0.2598 | 0.8063 | 0.7257 | 0.7639 | 0.9147 |
| No log | 5.0 | 165 | 0.2783 | 0.7927 | 0.7429 | 0.7670 | 0.9159 |
| No log | 6.0 | 198 | 0.2899 | 0.8019 | 0.74 | 0.7697 | 0.9165 |
| No log | 7.0 | 231 | 0.2925 | 0.7933 | 0.7457 | 0.7688 | 0.9147 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
