populism_classifier_bsample_176
This model is a fine-tuned version of AnonymousCS/populism_multilingual_bert_uncased_v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6123
- Accuracy: 0.7368
- 1-f1: 0.5133
- 1-recall: 1.0
- 1-precision: 0.3452
- Balanced Acc: 0.8472
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 |
|---|---|---|---|---|---|---|---|---|
| 0.1185 | 1.0 | 5 | 1.0444 | 0.6316 | 0.4296 | 1.0 | 0.2736 | 0.7861 |
| 0.0433 | 2.0 | 10 | 0.4482 | 0.8086 | 0.5918 | 1.0 | 0.4203 | 0.8889 |
| 0.012 | 3.0 | 15 | 0.3738 | 0.8373 | 0.6136 | 0.9310 | 0.4576 | 0.8766 |
| 0.0211 | 4.0 | 20 | 0.4960 | 0.7751 | 0.5524 | 1.0 | 0.3816 | 0.8694 |
| 0.0395 | 5.0 | 25 | 0.6123 | 0.7368 | 0.5133 | 1.0 | 0.3452 | 0.8472 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Model tree for AnonymousCS/populism_classifier_bsample_176
Base model
google-bert/bert-base-multilingual-uncased