populism_model325
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: 0.2307
- Accuracy: 0.9889
- 1-f1: 0.8
- 1-recall: 0.7857
- 1-precision: 0.8148
- Balanced Acc: 0.8903
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 |
---|---|---|---|---|---|---|---|---|
0.2419 | 1.0 | 124 | 0.1669 | 0.9858 | 0.75 | 0.75 | 0.75 | 0.8714 |
0.1222 | 2.0 | 248 | 0.1828 | 0.9848 | 0.7458 | 0.7857 | 0.7097 | 0.8882 |
0.0257 | 3.0 | 372 | 0.2307 | 0.9889 | 0.8 | 0.7857 | 0.8148 | 0.8903 |
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