populism_model109
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: 0.3827
- Accuracy: 0.9004
- 1-f1: 0.2535
- 1-recall: 0.4737
- 1-precision: 0.1731
- Balanced Acc: 0.6949
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: 128
- eval_batch_size: 128
- 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 |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 17 | 0.4790 | 0.8195 | 0.1864 | 0.5789 | 0.1111 | 0.7037 |
0.5167 | 2.0 | 34 | 0.4572 | 0.8026 | 0.1732 | 0.5789 | 0.1019 | 0.6949 |
0.3953 | 3.0 | 51 | 0.4053 | 0.9154 | 0.2623 | 0.4211 | 0.1905 | 0.6774 |
0.3953 | 4.0 | 68 | 0.3964 | 0.8872 | 0.25 | 0.5263 | 0.1639 | 0.7135 |
0.3107 | 5.0 | 85 | 0.3827 | 0.9004 | 0.2535 | 0.4737 | 0.1731 | 0.6949 |
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_model109
Base model
answerdotai/ModernBERT-base