| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: bert-base-multilingual-uncased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - precision |
| - recall |
| - f1 |
| model-index: |
| - name: SA_Model_bert-base-multilingual-uncased |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # SA_Model_bert-base-multilingual-uncased |
|
|
| This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6256 |
| - Accuracy: 0.9000 |
| - Precision: 0.8995 |
| - Recall: 0.9000 |
| - F1: 0.8998 |
|
|
| ## 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 |
| - lr_scheduler_warmup_steps: 100 |
| - num_epochs: 6 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:| |
| | 0.4675 | 1.0 | 2004 | 0.3975 | 0.8631 | 0.8637 | 0.8631 | 0.8630 | |
| | 0.36 | 2.0 | 4008 | 0.3589 | 0.8695 | 0.8781 | 0.8695 | 0.8719 | |
| | 0.2715 | 3.0 | 6012 | 0.4023 | 0.8822 | 0.8840 | 0.8822 | 0.8828 | |
| | 0.222 | 4.0 | 8016 | 0.4390 | 0.8917 | 0.8925 | 0.8917 | 0.8920 | |
| | 0.151 | 5.0 | 10020 | 0.5550 | 0.8994 | 0.8984 | 0.8994 | 0.8981 | |
| | 0.1544 | 6.0 | 12024 | 0.6256 | 0.9000 | 0.8995 | 0.9000 | 0.8998 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - Pytorch 2.12.0+cu130 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
| |
