populism_model119
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: 0.3623
- Accuracy: 0.9112
- 1-f1: 0.4103
- 1-recall: 0.7273
- 1-precision: 0.2857
- Balanced Acc: 0.8233
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: 64
- eval_batch_size: 64
- 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 | 1-f1 | 1-recall | 1-precision | Balanced Acc |
---|---|---|---|---|---|---|---|---|
0.4805 | 1.0 | 33 | 0.3932 | 0.8707 | 0.3495 | 0.8182 | 0.2222 | 0.8456 |
0.4384 | 2.0 | 66 | 0.3819 | 0.8398 | 0.3140 | 0.8636 | 0.1919 | 0.8512 |
0.3546 | 3.0 | 99 | 0.3564 | 0.8822 | 0.3838 | 0.8636 | 0.2468 | 0.8734 |
0.2639 | 4.0 | 132 | 0.3752 | 0.8494 | 0.3276 | 0.8636 | 0.2021 | 0.8562 |
0.2525 | 5.0 | 165 | 0.3623 | 0.9112 | 0.4103 | 0.7273 | 0.2857 | 0.8233 |
Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for AnonymousCS/populism_model119
Base model
answerdotai/ModernBERT-base