populism_classifier_bsample_003
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6809
- Accuracy: 0.7692
- 1-f1: 0.3910
- 1-recall: 0.8667
- 1-precision: 0.2524
- Balanced Acc: 0.8134
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: 32
- eval_batch_size: 32
- 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: 20
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.1154 | 1.0 | 6 | 0.7949 | 0.7322 | 0.3562 | 0.8667 | 0.2241 | 0.7931 |
| 0.1149 | 2.0 | 12 | 0.6876 | 0.7578 | 0.3704 | 0.8333 | 0.2381 | 0.7921 |
| 0.1005 | 3.0 | 18 | 0.5583 | 0.7977 | 0.4034 | 0.8 | 0.2697 | 0.7988 |
| 0.015 | 4.0 | 24 | 0.6372 | 0.7664 | 0.3881 | 0.8667 | 0.25 | 0.8118 |
| 0.0281 | 5.0 | 30 | 0.6809 | 0.7692 | 0.3910 | 0.8667 | 0.2524 | 0.8134 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-bert/bert-base-multilingual-cased