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bert-base-german-cased-noisy-pretrain-fine-tuned_v2
This model is a fine-tuned version of tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2872
- Precision: 0.7870
- Recall: 0.76
- F1: 0.7733
- Accuracy: 0.9159
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 | 0.3105 | 0.7731 | 0.5743 | 0.6590 | 0.8813 |
| No log | 2.0 | 66 | 0.2632 | 0.7588 | 0.7371 | 0.7478 | 0.9055 |
| No log | 3.0 | 99 | 0.2517 | 0.7630 | 0.7543 | 0.7586 | 0.9096 |
| No log | 4.0 | 132 | 0.2590 | 0.8145 | 0.74 | 0.7754 | 0.9171 |
| No log | 5.0 | 165 | 0.2665 | 0.7939 | 0.7486 | 0.7706 | 0.9165 |
| No log | 6.0 | 198 | 0.2854 | 0.7951 | 0.7429 | 0.7681 | 0.9147 |
| No log | 7.0 | 231 | 0.2872 | 0.7870 | 0.76 | 0.7733 | 0.9159 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
