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--- |
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library_name: transformers |
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license: mit |
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base_model: AnonymousCS/populism_multilingual_roberta_base |
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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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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: populism_model57 |
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results: [] |
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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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# populism_model57 |
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This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4202 |
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- Accuracy: 0.9208 |
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- F1: 0.5349 |
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- Recall: 0.7419 |
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- Precision: 0.4182 |
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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: 1e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
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| 0.3172 | 1.0 | 64 | 0.2908 | 0.8930 | 0.4882 | 0.8306 | 0.3456 | |
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| 0.2509 | 2.0 | 128 | 0.3295 | 0.9173 | 0.5348 | 0.7742 | 0.4085 | |
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| 0.2087 | 3.0 | 192 | 0.3780 | 0.9178 | 0.5257 | 0.7419 | 0.4071 | |
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| 0.1541 | 4.0 | 256 | 0.4652 | 0.9287 | 0.5355 | 0.6694 | 0.4462 | |
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| 0.1453 | 5.0 | 320 | 0.4202 | 0.9208 | 0.5349 | 0.7419 | 0.4182 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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