populism_classifier_bsample_326
This model is a fine-tuned version of AnonymousCS/populism_english_bert_large_cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3846
- Accuracy: 0.9142
- 1-f1: 0.3602
- 1-recall: 0.9038
- 1-precision: 0.2249
- Balanced Acc: 0.9092
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 |
|---|---|---|---|---|---|---|---|---|
| 0.1223 | 1.0 | 19 | 0.3828 | 0.9281 | 0.4017 | 0.9038 | 0.2582 | 0.9163 |
| 0.0368 | 2.0 | 38 | 0.3491 | 0.9188 | 0.368 | 0.8846 | 0.2323 | 0.9022 |
| 0.0084 | 3.0 | 57 | 0.4493 | 0.9029 | 0.3368 | 0.9231 | 0.2060 | 0.9127 |
| 0.0034 | 4.0 | 76 | 0.3846 | 0.9142 | 0.3602 | 0.9038 | 0.2249 | 0.9092 |
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_326
Base model
google-bert/bert-large-cased