populism_classifier_bsample_384
This model is a fine-tuned version of AnonymousCS/populism_english_bert_large_uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7028
- Accuracy: 0.7177
- 1-f1: 0.4870
- 1-recall: 0.9655
- 1-precision: 0.3256
- Balanced Acc: 0.8216
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 |
|---|---|---|---|---|---|---|---|---|
| 0.2064 | 1.0 | 5 | 1.0067 | 0.6746 | 0.4603 | 1.0 | 0.2990 | 0.8111 |
| 0.0468 | 2.0 | 10 | 0.5315 | 0.7799 | 0.54 | 0.9310 | 0.3803 | 0.8433 |
| 0.0149 | 3.0 | 15 | 0.4827 | 0.8325 | 0.6067 | 0.9310 | 0.45 | 0.8739 |
| 0.0147 | 4.0 | 20 | 0.6328 | 0.7225 | 0.4912 | 0.9655 | 0.3294 | 0.8244 |
| 0.0208 | 5.0 | 25 | 0.7028 | 0.7177 | 0.4870 | 0.9655 | 0.3256 | 0.8216 |
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_384
Base model
google-bert/bert-large-uncased