populism_classifier_353
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: 0.4468
- Accuracy: 0.9263
- 1-f1: 0.5882
- 1-recall: 0.7692
- 1-precision: 0.4762
- Balanced Acc: 0.8535
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 |
|---|---|---|---|---|---|---|---|---|
| 0.2098 | 1.0 | 24 | 0.3538 | 0.9237 | 0.6027 | 0.8462 | 0.4681 | 0.8878 |
| 0.3321 | 2.0 | 48 | 0.3210 | 0.9158 | 0.5789 | 0.8462 | 0.44 | 0.8835 |
| 0.0678 | 3.0 | 72 | 0.4057 | 0.9395 | 0.6230 | 0.7308 | 0.5429 | 0.8428 |
| 0.0396 | 4.0 | 96 | 0.5666 | 0.95 | 0.6415 | 0.6538 | 0.6296 | 0.8128 |
| 0.0103 | 5.0 | 120 | 0.4468 | 0.9263 | 0.5882 | 0.7692 | 0.4762 | 0.8535 |
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_353
Base model
google-bert/bert-base-uncased