bert-base-multilingual-cased
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0149
- Precision: 0.9609
- Recall: 0.9685
- F1: 0.9647
- Accuracy: 0.9949
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 |
|---|
| No log | 1.0 | 109 | 0.0191 | 0.9354 | 0.9685 | 0.9516 | 0.9935 |
| No log | 2.0 | 218 | 0.0162 | 0.9606 | 0.9606 | 0.9606 | 0.9942 |
| No log | 3.0 | 327 | 0.0149 | 0.9609 | 0.9685 | 0.9647 | 0.9949 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3
