populism_model93
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: 0.7659
- Accuracy: 0.9244
- 1-f1: 0.3592
- 1-recall: 0.4353
- 1-precision: 0.3058
- Balanced Acc: 0.6923
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 |
---|---|---|---|---|---|---|---|---|
0.3779 | 1.0 | 110 | 0.4729 | 0.9020 | 0.3187 | 0.4706 | 0.2410 | 0.6973 |
0.3089 | 2.0 | 220 | 0.5169 | 0.9077 | 0.3264 | 0.4588 | 0.2532 | 0.6948 |
0.2595 | 3.0 | 330 | 0.4947 | 0.8842 | 0.2986 | 0.5059 | 0.2118 | 0.7047 |
0.1767 | 4.0 | 440 | 0.7978 | 0.9415 | 0.3544 | 0.3294 | 0.3836 | 0.6512 |
0.0985 | 5.0 | 550 | 0.7659 | 0.9244 | 0.3592 | 0.4353 | 0.3058 | 0.6923 |
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_model93
Base model
answerdotai/ModernBERT-base