populism_classifier_bsample_348
This model is a fine-tuned version of AnonymousCS/populism_english_bert_base_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0146
- Accuracy: 0.7761
- 1-f1: 0.1631
- 1-recall: 0.76
- 1-precision: 0.0913
- Balanced Acc: 0.7683
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0861 | 1.0 | 9 | 1.1858 | 0.6383 | 0.1322 | 0.96 | 0.0710 | 0.7944 |
| 0.0571 | 2.0 | 18 | 0.8912 | 0.7130 | 0.1497 | 0.88 | 0.0818 | 0.7940 |
| 0.162 | 3.0 | 27 | 0.8282 | 0.7727 | 0.1538 | 0.72 | 0.0861 | 0.7471 |
| 0.0176 | 4.0 | 36 | 1.0589 | 0.7474 | 0.1667 | 0.88 | 0.0921 | 0.8117 |
| 0.0268 | 5.0 | 45 | 1.0146 | 0.7761 | 0.1631 | 0.76 | 0.0913 | 0.7683 |
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_348
Base model
google-bert/bert-base-uncased