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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_model93 |
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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_model93 |
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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: 0.7659 |
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- Accuracy: 0.9244 |
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- 1-f1: 0.3592 |
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- 1-recall: 0.4353 |
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- 1-precision: 0.3058 |
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- Balanced Acc: 0.6923 |
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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: 64 |
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- eval_batch_size: 64 |
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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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| 0.3779 | 1.0 | 110 | 0.4729 | 0.9020 | 0.3187 | 0.4706 | 0.2410 | 0.6973 | |
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| 0.3089 | 2.0 | 220 | 0.5169 | 0.9077 | 0.3264 | 0.4588 | 0.2532 | 0.6948 | |
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| 0.2595 | 3.0 | 330 | 0.4947 | 0.8842 | 0.2986 | 0.5059 | 0.2118 | 0.7047 | |
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| 0.1767 | 4.0 | 440 | 0.7978 | 0.9415 | 0.3544 | 0.3294 | 0.3836 | 0.6512 | |
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| 0.0985 | 5.0 | 550 | 0.7659 | 0.9244 | 0.3592 | 0.4353 | 0.3058 | 0.6923 | |
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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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