populism_classifier_bsample_032
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: 0.6975
- Accuracy: 0.8125
- 1-f1: 0.3851
- 1-recall: 0.9394
- 1-precision: 0.2422
- Balanced Acc: 0.8717
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 |
---|---|---|---|---|---|---|---|---|
0.0138 | 1.0 | 8 | 0.7747 | 0.75 | 0.3265 | 0.9697 | 0.1963 | 0.8525 |
0.0265 | 2.0 | 16 | 0.7617 | 0.7803 | 0.3409 | 0.9091 | 0.2098 | 0.8404 |
0.0489 | 3.0 | 24 | 0.6448 | 0.8598 | 0.3934 | 0.7273 | 0.2697 | 0.7980 |
0.0109 | 4.0 | 32 | 0.7026 | 0.7973 | 0.3669 | 0.9394 | 0.2279 | 0.8636 |
0.0057 | 5.0 | 40 | 0.6975 | 0.8125 | 0.3851 | 0.9394 | 0.2422 | 0.8717 |
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_032
Base model
google-bert/bert-base-multilingual-uncased