populism_classifier_bsample_004
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3832
- Accuracy: 0.9233
- 1-f1: 0.3005
- 1-recall: 0.8286
- 1-precision: 0.1835
- Balanced Acc: 0.8769
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0488 | 1.0 | 15 | 0.3677 | 0.8949 | 0.2570 | 0.9143 | 0.1495 | 0.9044 |
| 0.0307 | 2.0 | 30 | 0.3366 | 0.9228 | 0.2842 | 0.7714 | 0.1742 | 0.8486 |
| 0.0073 | 3.0 | 45 | 0.3596 | 0.9216 | 0.2959 | 0.8286 | 0.1801 | 0.8760 |
| 0.0036 | 4.0 | 60 | 0.3832 | 0.9233 | 0.3005 | 0.8286 | 0.1835 | 0.8769 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
google-bert/bert-base-multilingual-cased