| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google-bert/bert-base-multilingual-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: intent-classifier-entity-executor |
| 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. --> |
|
|
| # intent-classifier-entity-executor |
|
|
| This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0020 |
| - Precision: 0.9990 |
| - Recall: 0.9991 |
| - F1: 0.9990 |
| - Accuracy: 0.9996 |
|
|
| ## 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: 32 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 5 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
| |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:| |
| | 0.0079 | 1.0 | 2922 | 0.0081 | 0.9932 | 0.9932 | 0.9932 | 0.9975 | |
| | 0.0056 | 2.0 | 5844 | 0.0040 | 0.9971 | 0.9969 | 0.9970 | 0.9989 | |
| | 0.002 | 3.0 | 8766 | 0.0021 | 0.9988 | 0.9986 | 0.9987 | 0.9995 | |
| | 0.0004 | 4.0 | 11688 | 0.0017 | 0.9989 | 0.9989 | 0.9989 | 0.9996 | |
| | 0.0003 | 5.0 | 14610 | 0.0020 | 0.9990 | 0.9991 | 0.9990 | 0.9996 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
|
|
