---
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: 0.1614
- F1: 0.7869
- F5: 0.8020
- Precision: 0.75
- Recall: 0.8276

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F5     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| No log        | 1.0   | 30   | 0.2615          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 60   | 0.1838          | 0.5333 | 0.4626 | 0.8889    | 0.3810 |
| No log        | 3.0   | 90   | 0.2338          | 0.3077 | 0.2491 | 0.8       | 0.1905 |
| No log        | 4.0   | 120  | 0.2003          | 0.6667 | 0.6268 | 0.8       | 0.5714 |
| No log        | 5.0   | 150  | 0.2643          | 0.5    | 0.4906 | 0.5263    | 0.4762 |
| No log        | 6.0   | 180  | 0.2211          | 0.6486 | 0.6168 | 0.75      | 0.5714 |
| No log        | 7.0   | 210  | 0.2233          | 0.6    | 0.6391 | 0.5172    | 0.7143 |
| No log        | 8.0   | 240  | 0.3328          | 0.5    | 0.5647 | 0.3846    | 0.7143 |


### Framework versions

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