populism_classifier_028
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1975
- Accuracy: 0.9377
- 1-f1: 0.5366
- 1-recall: 0.9167
- 1-precision: 0.3793
- Balanced Acc: 0.9276
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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.0595 | 1.0 | 20 | 0.2141 | 0.9705 | 0.6087 | 0.5833 | 0.6364 | 0.7848 |
| 0.2489 | 2.0 | 40 | 0.2365 | 0.9803 | 0.7 | 0.5833 | 0.875 | 0.7900 |
| 0.0331 | 3.0 | 60 | 0.1314 | 0.9443 | 0.5405 | 0.8333 | 0.4 | 0.8911 |
| 0.0369 | 4.0 | 80 | 0.1809 | 0.9672 | 0.6667 | 0.8333 | 0.5556 | 0.9030 |
| 0.0328 | 5.0 | 100 | 0.1975 | 0.9377 | 0.5366 | 0.9167 | 0.3793 | 0.9276 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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Base model
google-bert/bert-base-multilingual-uncased