populism_model300
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4478
- Accuracy: 0.9610
- 1-f1: 0.5641
- 1-recall: 0.5432
- 1-precision: 0.5867
- Balanced Acc: 0.7623
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 OptimizerNames.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: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
---|---|---|---|---|---|---|---|---|
0.3152 | 1.0 | 219 | 0.4151 | 0.9622 | 0.4844 | 0.3827 | 0.6596 | 0.6866 |
0.2534 | 2.0 | 438 | 0.3783 | 0.9622 | 0.5714 | 0.5432 | 0.6027 | 0.7629 |
0.1255 | 3.0 | 657 | 0.4478 | 0.9610 | 0.5641 | 0.5432 | 0.5867 | 0.7623 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
google-bert/bert-base-multilingual-uncased