---
license: apache-2.0
base_model: bert-base-multilingual-cased
tags:
- generated_from_trainer
datasets:
- wikiann
model-index:
- name: fine_tuned_BERT_cs_wikann
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# fine_tuned_BERT_cs_wikann

This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the wikiann dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1428
- Overall Precision: 0.9090
- Overall Recall: 0.9274
- Overall F1: 0.9181
- Overall Accuracy: 0.9673

## 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
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 0.3011        | 0.4   | 500  | 0.1781          | 0.8588            | 0.8721         | 0.8654     | 0.9501           |
| 0.1717        | 0.8   | 1000 | 0.1524          | 0.8733            | 0.9033         | 0.8880     | 0.9565           |
| 0.1307        | 1.2   | 1500 | 0.1443          | 0.9058            | 0.9051         | 0.9054     | 0.9639           |
| 0.0968        | 1.6   | 2000 | 0.1392          | 0.9075            | 0.9107         | 0.9091     | 0.9651           |
| 0.0974        | 2.0   | 2500 | 0.1352          | 0.9030            | 0.9201         | 0.9115     | 0.9647           |
| 0.0603        | 2.4   | 3000 | 0.1410          | 0.9091            | 0.9217         | 0.9154     | 0.9667           |
| 0.054         | 2.8   | 3500 | 0.1428          | 0.9090            | 0.9274         | 0.9181     | 0.9673           |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.15.0