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--- |
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license: apache-2.0 |
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base_model: bert-base-multilingual-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert-base-multilingual-cased-fire-classification-silvanus |
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results: [] |
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widget: |
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- text: >- |
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Kebakaran hutan dan lahan terus terjadi dan semakin meluas di Kota |
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Palangkaraya, Kalimantan Tengah (Kalteng) pada hari Rabu, 15 Nopember 2023 |
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20.00 WIB. Bahkan kobaran api mulai membakar pondok warga dan mendekati |
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permukiman. BZK #RCTINews #SeputariNews #News #Karhutla #KebakaranHutan |
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#HutanKalimantan #SILVANUS_Italian_Pilot_Testing |
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example_title: Indonesia |
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- text: >- |
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Wildfire rages for a second day in Evia destroying a Natura 2000 protected |
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pine forest. - 5:51 PM Aug 14, 2019 |
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example_title: English |
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- text: >- |
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3 nov 2023 21:57 - Incendio forestal obliga a la evacuación de hasta 850 |
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personas cerca del pueblo de Montichelvo en Valencia. |
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example_title: Spanish |
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- text: >- |
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Incendi boschivi nell'est del Paese: 2 morti e oltre 50 case distrutte nello |
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stato del Queensland. |
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example_title: Italian |
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- text: >- |
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Lesné požiare na Sicílii si vyžiadali dva ľudské životy a evakuáciu hotela |
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http://dlvr.it/SwW3sC - 23. septembra 2023 20:57 |
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example_title: Slovak |
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language: |
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- id |
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- en |
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- es |
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- it |
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- sk |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-base-multilingual-cased-fire-classification-silvanus |
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This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3171 |
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- Accuracy: 0.9185 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 233 | 0.2618 | 0.9056 | |
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| No log | 2.0 | 466 | 0.2923 | 0.9142 | |
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| 0.3256 | 3.0 | 699 | 0.3171 | 0.9185 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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