---
base_model: google-bert/bert-base-multilingual-cased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
- precision
- recall
tags:
- generated_from_trainer
model-index:
- name: bert-base-multilingual-cased-intent-booking
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-multilingual-cased-intent-booking

This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3045
- Accuracy: 0.9189
- F1: 0.9155
- Precision: 0.9322
- Recall: 0.9189

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 64
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 2.246         | 1.0   | 65   | 1.7430          | 0.4730   | 0.3680 | 0.3529    | 0.4730 |
| 0.972         | 2.0   | 130  | 0.3620          | 0.9369   | 0.9371 | 0.9417    | 0.9369 |
| 0.3069        | 3.0   | 195  | 0.2379          | 0.9414   | 0.9412 | 0.9490    | 0.9414 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1