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library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_004
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# populism_classifier_004
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2928
- Accuracy: 0.9833
- 1-f1: 0.5312
- 1-recall: 0.5667
- 1-precision: 0.5
- Balanced Acc: 0.7785
## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2697 | 1.0 | 57 | 0.1656 | 0.9855 | 0.5806 | 0.6 | 0.5625 | 0.7960 |
| 0.0992 | 2.0 | 114 | 0.1429 | 0.9699 | 0.46 | 0.7667 | 0.3286 | 0.8700 |
| 0.1229 | 3.0 | 171 | 0.1970 | 0.9805 | 0.4776 | 0.5333 | 0.4324 | 0.7607 |
| 0.0171 | 4.0 | 228 | 0.2928 | 0.9833 | 0.5312 | 0.5667 | 0.5 | 0.7785 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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