---
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: 0.1299
- F1: 0.8444
- F5: 0.8373
- Precision: 0.8636
- Recall: 0.8261

## 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
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | F5     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
| No log        | 1.0   | 33   | 0.3776          | 0.0    | 0.0    | 0.0       | 0.0    |
| No log        | 2.0   | 66   | 0.2996          | 0.4    | 0.3359 | 0.8       | 0.2667 |
| No log        | 3.0   | 99   | 0.2137          | 0.7273 | 0.7534 | 0.6667    | 0.8    |
| No log        | 4.0   | 132  | 0.2161          | 0.6429 | 0.6258 | 0.6923    | 0.6    |
| No log        | 5.0   | 165  | 0.2367          | 0.6154 | 0.5812 | 0.7273    | 0.5333 |
| No log        | 6.0   | 198  | 0.1997          | 0.7451 | 0.6980 | 0.9048    | 0.6333 |
| No log        | 7.0   | 231  | 0.2023          | 0.8000 | 0.8    | 0.8       | 0.8    |
| No log        | 8.0   | 264  | 0.2011          | 0.8070 | 0.7911 | 0.8519    | 0.7667 |
| No log        | 9.0   | 297  | 0.2196          | 0.7857 | 0.7648 | 0.8462    | 0.7333 |
| No log        | 10.0  | 330  | 0.2509          | 0.7667 | 0.7667 | 0.7667    | 0.7667 |


### Framework versions

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