populism_classifier_bsample_155
This model is a fine-tuned version of AnonymousCS/populism_multilingual_bert_cased_v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7143
- Accuracy: 0.9008
- 1-f1: 0.4248
- 1-recall: 0.6486
- 1-precision: 0.3158
- Balanced Acc: 0.7823
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 |
|---|---|---|---|---|---|---|---|---|
| 0.3495 | 1.0 | 9 | 0.7115 | 0.8214 | 0.3464 | 0.8378 | 0.2183 | 0.8291 |
| 0.0867 | 2.0 | 18 | 0.8843 | 0.7664 | 0.3014 | 0.8919 | 0.1813 | 0.8254 |
| 0.0133 | 3.0 | 27 | 0.6226 | 0.8443 | 0.3704 | 0.8108 | 0.24 | 0.8285 |
| 0.0069 | 4.0 | 36 | 0.7904 | 0.7939 | 0.3284 | 0.8919 | 0.2012 | 0.8400 |
| 0.0861 | 5.0 | 45 | 0.7143 | 0.9008 | 0.4248 | 0.6486 | 0.3158 | 0.7823 |
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_155
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google-bert/bert-base-multilingual-cased