populism_classifier_bsample_401
This model is a fine-tuned version of google/rembert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7541
- Accuracy: 0.8675
- 1-f1: 0.4593
- 1-recall: 0.9688
- 1-precision: 0.3010
- Balanced Acc: 0.9150
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 |
---|---|---|---|---|---|---|---|---|
0.1705 | 1.0 | 6 | 0.8757 | 0.7550 | 0.3216 | 1.0 | 0.1916 | 0.8699 |
0.0318 | 2.0 | 12 | 0.2496 | 0.9365 | 0.6154 | 0.875 | 0.4746 | 0.9076 |
0.0026 | 3.0 | 18 | 0.5881 | 0.8748 | 0.4733 | 0.9688 | 0.3131 | 0.9189 |
0.0028 | 4.0 | 24 | 0.7541 | 0.8675 | 0.4593 | 0.9688 | 0.3010 | 0.9150 |
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/rembert