populism_model107
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: 0.6526
- Accuracy: 0.6515
- 1-f1: 0.3429
- 1-recall: 0.6667
- 1-precision: 0.2308
- Balanced Acc: 0.6579
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 | 7 | 0.6806 | 0.6515 | 0.3168 | 0.5926 | 0.2162 | 0.6267 |
No log | 2.0 | 14 | 0.6845 | 0.6313 | 0.3303 | 0.6667 | 0.2195 | 0.6462 |
No log | 3.0 | 21 | 0.6554 | 0.6566 | 0.3462 | 0.6667 | 0.2338 | 0.6608 |
No log | 4.0 | 28 | 0.6491 | 0.6465 | 0.3396 | 0.6667 | 0.2278 | 0.6550 |
No log | 5.0 | 35 | 0.6526 | 0.6515 | 0.3429 | 0.6667 | 0.2308 | 0.6579 |
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_model107
Base model
answerdotai/ModernBERT-base