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bert-base-multilingual-cased
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0401
- Precision: 0.9722
- Recall: 0.9767
- F1: 0.9744
- Accuracy: 0.9921
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.14 | 1.0 | 963 | 0.0499 | 0.9376 | 0.9521 | 0.9448 | 0.9840 |
| 0.0258 | 2.0 | 1926 | 0.0453 | 0.9589 | 0.9699 | 0.9644 | 0.9903 |
| 0.0114 | 3.0 | 2889 | 0.0401 | 0.9722 | 0.9767 | 0.9744 | 0.9921 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2
