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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: google/rembert |
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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: populism_classifier_416 |
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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_classifier_416 |
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This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6585 |
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- Accuracy: 0.9371 |
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- 1-f1: 0.0 |
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- 1-recall: 0.0 |
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- 1-precision: 0.0 |
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- Balanced Acc: 0.5 |
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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: 16 |
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- eval_batch_size: 32 |
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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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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 20 |
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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 | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:| |
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| 0.1819 | 1.0 | 124 | 0.6633 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.4154 | 2.0 | 248 | 0.6913 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.6373 | 3.0 | 372 | 0.6449 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.4658 | 4.0 | 496 | 0.6969 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 1.0914 | 5.0 | 620 | 0.7048 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.3045 | 6.0 | 744 | 0.6476 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.7046 | 7.0 | 868 | 0.6569 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.3645 | 8.0 | 992 | 0.6368 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.2303 | 9.0 | 1116 | 0.6604 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.5905 | 10.0 | 1240 | 0.6307 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.3306 | 11.0 | 1364 | 0.6332 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.2381 | 12.0 | 1488 | 0.6957 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.4752 | 13.0 | 1612 | 0.6574 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.6578 | 14.0 | 1736 | 0.6515 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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| 0.5788 | 15.0 | 1860 | 0.6585 | 0.9371 | 0.0 | 0.0 | 0.0 | 0.5 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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