bert-base-german-cased-noisy-pretrain-fine-tuned_v1.2
This model is a fine-tuned version of tbosse/bert-base-german-cased-finetuned-subj_preTrained_with_noisyData_v1.2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2810
- Precision: 0.7874
- Recall: 0.7514
- F1: 0.7690
- 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 | 0.3078 | 0.7675 | 0.5943 | 0.6699 | 0.8842 |
No log | 2.0 | 66 | 0.2535 | 0.7729 | 0.7486 | 0.7605 | 0.9073 |
No log | 3.0 | 99 | 0.2417 | 0.7714 | 0.7714 | 0.7714 | 0.9119 |
No log | 4.0 | 132 | 0.2532 | 0.8031 | 0.7343 | 0.7672 | 0.9142 |
No log | 5.0 | 165 | 0.2675 | 0.7834 | 0.7543 | 0.7686 | 0.9142 |
No log | 6.0 | 198 | 0.2750 | 0.7870 | 0.76 | 0.7733 | 0.9159 |
No log | 7.0 | 231 | 0.2810 | 0.7874 | 0.7514 | 0.7690 | 0.9147 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
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