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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_411 |
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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_411 |
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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: 0.7307 |
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- Accuracy: 0.9091 |
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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: 0.4985 |
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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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| 0.5911 | 1.0 | 91 | 0.7011 | 0.1515 | 0.1720 | 1.0 | 0.0941 | 0.5347 | |
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| 0.6288 | 2.0 | 182 | 0.8307 | 0.0882 | 0.1620 | 1.0 | 0.0882 | 0.5 | |
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| 0.5907 | 3.0 | 273 | 0.6749 | 0.2011 | 0.1808 | 1.0 | 0.0994 | 0.5619 | |
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| 0.675 | 4.0 | 364 | 0.7471 | 0.0909 | 0.1624 | 1.0 | 0.0884 | 0.5015 | |
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| 0.8407 | 5.0 | 455 | 0.9201 | 0.0882 | 0.1620 | 1.0 | 0.0882 | 0.5 | |
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| 0.625 | 6.0 | 546 | 0.6675 | 0.8375 | 0.1449 | 0.1562 | 0.1351 | 0.5298 | |
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| 0.383 | 7.0 | 637 | 0.6634 | 0.6860 | 0.1972 | 0.4375 | 0.1273 | 0.5737 | |
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| 1.0487 | 8.0 | 728 | 0.6541 | 0.7879 | 0.2524 | 0.4062 | 0.1831 | 0.6155 | |
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| 0.655 | 9.0 | 819 | 0.8689 | 0.8485 | 0.0678 | 0.0625 | 0.0741 | 0.4935 | |
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| 0.7175 | 10.0 | 910 | 0.6738 | 0.8981 | 0.0 | 0.0 | 0.0 | 0.4924 | |
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| 0.4837 | 11.0 | 1001 | 0.7142 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 | |
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| 0.257 | 12.0 | 1092 | 0.8252 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 | |
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| 0.7864 | 13.0 | 1183 | 0.7307 | 0.9091 | 0.0 | 0.0 | 0.0 | 0.4985 | |
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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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