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---
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
- Silvanus
metrics:
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-language-detection-silvanus
  results: []
datasets:
- rollerhafeezh-amikom/language-detection
language:
- id
- en
- es
- it
- sk
widget:
- text: >-
    Kebakaran hutan dan lahan terus terjadi dan semakin meluas di Kota
    Palangkaraya, Kalimantan Tengah (Kalteng) pada hari Rabu, 15 Nopember 2023
    20.00 WIB. Bahkan kobaran api mulai membakar pondok warga dan mendekati
    permukiman. BZK #RCTINews #SeputariNews #News #Karhutla #KebakaranHutan
    #HutanKalimantan #SILVANUS_Italian_Pilot_Testing
  example_title: Indonesia
- text: >-
    Wildfire rages for a second day in Evia destroying a Natura 2000 protected
    pine forest. - 5:51 PM Aug 14, 2019
  example_title: English
- text: >-
    3 nov 2023 21:57 - Incendio forestal obliga a la evacuación de hasta 850
    personas cerca del pueblo de Montichelvo en Valencia.
  example_title: Spanish
- text: >-
    Incendi boschivi nell'est del Paese: 2 morti e oltre 50 case distrutte nello
    stato del Queensland.
  example_title: Italian
- text: >-
    Lesné požiare na Sicílii si vyžiadali dva ľudské životy a evakuáciu hotela
    http://dlvr.it/SwW3sC - 23. septembra 2023 20:57
  example_title: Slovak
---

<!-- 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. -->

# distilbert-base-multilingual-cased-language-detection-silvanus

This model is a fine-tuned version of [distilbert/distilbert-base-multilingual-cased](https://huggingface.co/distilbert/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0268
- Accuracy: 0.9960

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 274  | 0.0342          | 0.9940   |
| 0.1401        | 2.0   | 548  | 0.0270          | 0.9960   |
| 0.1401        | 3.0   | 822  | 0.0268          | 0.9960   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1