---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
  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. -->

# results

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2090
- Accuracy: 0.9467
- F1: 0.9463
- Precision: 0.9469
- Recall: 0.9467

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.4561        | 1.0   | 1098  | 0.3688          | 0.8738   | 0.8709 | 0.8760    | 0.8738 |
| 0.3126        | 2.0   | 2196  | 0.2254          | 0.9339   | 0.9335 | 0.9340    | 0.9339 |
| 0.3852        | 3.0   | 3294  | 0.3113          | 0.9280   | 0.9274 | 0.9284    | 0.9280 |
| 0.2341        | 4.0   | 4392  | 0.2376          | 0.9417   | 0.9417 | 0.9418    | 0.9417 |
| 0.2108        | 5.0   | 5490  | 0.2433          | 0.9408   | 0.9407 | 0.9407    | 0.9408 |
| 0.0882        | 6.0   | 6588  | 0.2353          | 0.9371   | 0.9364 | 0.9384    | 0.9371 |
| 0.127         | 7.0   | 7686  | 0.2674          | 0.9276   | 0.9270 | 0.9277    | 0.9276 |
| 0.1413        | 8.0   | 8784  | 0.2859          | 0.9339   | 0.9341 | 0.9344    | 0.9339 |
| 0.7061        | 9.0   | 9882  | 0.6121          | 0.6761   | 0.5834 | 0.7861    | 0.6761 |
| 0.2076        | 10.0  | 10980 | 0.2090          | 0.9467   | 0.9463 | 0.9469    | 0.9467 |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.15.2