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--- |
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license: mit |
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base_model: xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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model-index: |
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- name: dutch_genre_classifier |
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results: [] |
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language: |
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- nl |
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pipeline_tag: text-classification |
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widget: |
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- text: We zullen zien bij de \#verkiezingen2024 |
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example_title: tw |
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- text: Meneer de minister, stemt u voor of tegen dit wetsvoorstel? |
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example_title: par |
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- text: Annie Geeraerts (97) en Ray Verhaeghe (97) werden recent nog officieel gehuldigd als het oudste soapkoppel ter wereld. Ook in 2024 denken ze nog niet aan stoppen. “Toen ik in het begin een contract van drie maanden kreeg vond ik dat al fantastisch lang, niet wetende dat het 32 jaar zou duren”, zegt Annie fier. “Het enige jammere is dat Albert nauwelijks nog zijn typische borreltjes mag drinken”, voegt Ray eraan toe. Showbits-reporter Jarne hoort het olijke duo uit over wat hun personages betekenen voor de trouwe soapfans. |
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example_title: nws |
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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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# dutch_genre_classifier |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1404 |
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- Precision: 0.9713 |
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- Recall: 0.9707 |
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- Fscore: 0.9707 |
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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: 3e-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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 2.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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### Framework versions |
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- Transformers 4.36.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
