---
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_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. -->

# fine_tuned_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: 0.1259
- F1: 0.8182
- F5: 0.8326
- Precision: 0.7826
- Recall: 0.8571

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F5     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| No log        | 1.0   | 65   | 0.2964          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 130  | 0.2682          | 0.4737 | 0.4081 | 0.8182    | 0.3333 |
| No log        | 3.0   | 195  | 0.2208          | 0.65   | 0.7421 | 0.4906    | 0.9630 |
| No log        | 4.0   | 260  | 0.1924          | 0.7273 | 0.7816 | 0.6154    | 0.8889 |
| No log        | 5.0   | 325  | 0.1246          | 0.8727 | 0.8788 | 0.8571    | 0.8889 |
| No log        | 6.0   | 390  | 0.1142          | 0.8519 | 0.8519 | 0.8519    | 0.8519 |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2