---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- f1
- recall
- accuracy
- precision
model-index:
- name: bert-base-fine-tuned-text-classificarion-ds-dropout
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-fine-tuned-text-classificarion-ds-dropout

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0721
- F1: 0.7307
- Recall: 0.7499
- Accuracy: 0.7499
- Precision: 0.7427

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
| No log        | 1.0   | 442  | 2.6972          | 0.4056 | 0.4819 | 0.4819   | 0.4782    |
| 3.5527        | 2.0   | 884  | 1.6292          | 0.5981 | 0.6559 | 0.6559   | 0.6035    |
| 2.1075        | 3.0   | 1326 | 1.2669          | 0.6801 | 0.7117 | 0.7117   | 0.6923    |
| 1.2767        | 4.0   | 1768 | 1.0995          | 0.7133 | 0.7437 | 0.7437   | 0.7336    |
| 0.9148        | 5.0   | 2210 | 1.0721          | 0.7307 | 0.7499 | 0.7499   | 0.7427    |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3