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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: bert-base-multilingual-uncased-finetuned-news
  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. -->

# bert-base-multilingual-uncased-finetuned-news

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5705
- Accuracy: 0.8896
- F1: 0.8904

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.5702        | 1.0   | 159  | 0.5156          | 0.7445   | 0.7553 |
| 0.3384        | 2.0   | 318  | 0.2883          | 0.8612   | 0.8641 |
| 0.2045        | 3.0   | 477  | 0.3699          | 0.8991   | 0.8977 |
| 0.1177        | 4.0   | 636  | 0.5172          | 0.8959   | 0.8969 |
| 0.0465        | 5.0   | 795  | 0.5705          | 0.8896   | 0.8904 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2