metadata
library_name: transformers
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: results
results: []
results
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0995
- Accuracy: 0.9724
- Precision: 0.9731
- Recall: 0.9724
- F1: 0.9724
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1995 | 1.0 | 172 | 0.1873 | 0.9507 | 0.9508 | 0.9507 | 0.9505 |
| 0.1341 | 2.0 | 344 | 0.1119 | 0.9666 | 0.9670 | 0.9666 | 0.9666 |
| 0.0784 | 3.0 | 516 | 0.0995 | 0.9724 | 0.9731 | 0.9724 | 0.9724 |
| 0.0609 | 4.0 | 688 | 0.1330 | 0.9623 | 0.9623 | 0.9623 | 0.9623 |
| 0.0434 | 5.0 | 860 | 0.1333 | 0.9637 | 0.9638 | 0.9637 | 0.9637 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0