---
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