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---
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 |
### Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
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