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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_model107 |
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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_model107 |
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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: 0.6526 |
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- Accuracy: 0.6515 |
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- 1-f1: 0.3429 |
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- 1-recall: 0.6667 |
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- 1-precision: 0.2308 |
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- Balanced Acc: 0.6579 |
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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 | 7 | 0.6806 | 0.6515 | 0.3168 | 0.5926 | 0.2162 | 0.6267 | |
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| No log | 2.0 | 14 | 0.6845 | 0.6313 | 0.3303 | 0.6667 | 0.2195 | 0.6462 | |
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| No log | 3.0 | 21 | 0.6554 | 0.6566 | 0.3462 | 0.6667 | 0.2338 | 0.6608 | |
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| No log | 4.0 | 28 | 0.6491 | 0.6465 | 0.3396 | 0.6667 | 0.2278 | 0.6550 | |
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| No log | 5.0 | 35 | 0.6526 | 0.6515 | 0.3429 | 0.6667 | 0.2308 | 0.6579 | |
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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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