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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: answerdotai/ModernBERT-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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model-index: |
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- name: populism_model111 |
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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_model111 |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6324 |
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- Accuracy: 0.9331 |
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- 1-f1: 0.3077 |
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- 1-recall: 0.3810 |
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- 1-precision: 0.2581 |
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- Balanced Acc: 0.6682 |
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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 | 1-f1 | 1-recall | 1-precision | Balanced Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:| |
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| No log | 1.0 | 17 | 0.4979 | 0.9554 | 0.0769 | 0.0476 | 0.2 | 0.5199 | |
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| 0.4627 | 2.0 | 34 | 0.4936 | 0.9424 | 0.3404 | 0.3810 | 0.3077 | 0.6731 | |
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| 0.2898 | 3.0 | 51 | 0.5184 | 0.9015 | 0.2535 | 0.4286 | 0.18 | 0.6746 | |
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| 0.2898 | 4.0 | 68 | 0.5747 | 0.9145 | 0.2581 | 0.3810 | 0.1951 | 0.6586 | |
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| 0.2036 | 5.0 | 85 | 0.6324 | 0.9331 | 0.3077 | 0.3810 | 0.2581 | 0.6682 | |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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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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