populism_classifier_365
This model is a fine-tuned version of AnonymousCS/populism_english_bert_large_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.8041
- Accuracy: 0.9541
- 1-f1: 0.4814
- 1-recall: 0.4466
- 1-precision: 0.5220
- Balanced Acc: 0.7131
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 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 |
|---|---|---|---|---|---|---|---|---|
| 0.4578 | 1.0 | 871 | 0.3614 | 0.8890 | 0.3760 | 0.7008 | 0.2569 | 0.7996 |
| 0.1728 | 2.0 | 1742 | 0.3576 | 0.9030 | 0.4207 | 0.7383 | 0.2942 | 0.8248 |
| 0.1014 | 3.0 | 2613 | 0.5243 | 0.9325 | 0.4268 | 0.5263 | 0.3590 | 0.7396 |
| 0.2324 | 4.0 | 3484 | 0.7760 | 0.9530 | 0.4696 | 0.4361 | 0.5088 | 0.7075 |
| 0.2645 | 5.0 | 4355 | 0.8041 | 0.9541 | 0.4814 | 0.4466 | 0.5220 | 0.7131 |
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_365
Base model
google-bert/bert-large-uncased