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

# m-bert

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: 0.3141
- Precison: 0.8543
- Recall: 0.8566
- F1: 0.8554
- Accuracy: 0.8594
- Jaccard: 0.7848

## 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: 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precison | Recall | F1     | Accuracy | Jaccard |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:--------:|:-------:|
| 0.4088        | 1.0   | 1513 | 0.3141          | 0.8543   | 0.8566 | 0.8554 | 0.8594   | 0.7848  |
| 0.3328        | 2.0   | 3026 | 0.3161          | 0.8685   | 0.8530 | 0.8587 | 0.8656   | 0.8018  |
| 0.2521        | 3.0   | 4539 | 0.3444          | 0.8729   | 0.8700 | 0.8714 | 0.8758   | 0.8105  |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1