populism_model105
This model is a fine-tuned version of answerdotai/ModernBERT-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6150
- Accuracy: 0.8237
- F1: 0.3333
- Recall: 0.5517
- Precision: 0.2388
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|---|---|---|---|---|---|---|---|
| 0.6904 | 1.0 | 91 | 0.5828 | 0.7025 | 0.2603 | 0.6552 | 0.1624 |
| 0.5919 | 2.0 | 182 | 0.5618 | 0.8292 | 0.2955 | 0.4483 | 0.2203 |
| 0.6766 | 3.0 | 273 | 0.5231 | 0.7603 | 0.3359 | 0.7586 | 0.2157 |
| 0.4499 | 4.0 | 364 | 0.5563 | 0.7906 | 0.3333 | 0.6552 | 0.2235 |
| 0.3823 | 5.0 | 455 | 0.6150 | 0.8237 | 0.3333 | 0.5517 | 0.2388 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
answerdotai/ModernBERT-base