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

# fine_tuned_mBERT

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: 0.0431
- F1: 0.8182
- F5: 0.8792
- Precision: 0.6923
- Recall: 1.0

## 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: 2.5e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F5     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| No log        | 1.0   | 16   | 0.2406          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 32   | 0.2933          | 0.6471 | 0.6062 | 0.7857    | 0.55   |
| No log        | 3.0   | 48   | 0.1965          | 0.5000 | 0.4297 | 0.875     | 0.35   |
| No log        | 4.0   | 64   | 0.1349          | 0.6842 | 0.6707 | 0.7222    | 0.65   |
| No log        | 5.0   | 80   | 0.1065          | 0.7027 | 0.6816 | 0.7647    | 0.65   |
| No log        | 6.0   | 96   | 0.1104          | 0.7727 | 0.8005 | 0.7083    | 0.85   |
| No log        | 7.0   | 112  | 0.1160          | 0.7273 | 0.7534 | 0.6667    | 0.8    |
| No log        | 8.0   | 128  | 0.1049          | 0.7647 | 0.7164 | 0.9286    | 0.65   |
| No log        | 9.0   | 144  | 0.0975          | 0.7778 | 0.7461 | 0.875     | 0.7    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.3.0a0+ebedce2
- Datasets 2.17.1
- Tokenizers 0.15.2