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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_014
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_014
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: 0.2774
- Accuracy: 0.9894
- 1-f1: 0.8108
- 1-recall: 0.7895
- 1-precision: 0.8333
- Balanced Acc: 0.8924
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0278 | 1.0 | 62 | 0.1071 | 0.9899 | 0.8361 | 0.8947 | 0.7846 | 0.9437 |
| 0.044 | 2.0 | 124 | 0.0920 | 0.9904 | 0.8455 | 0.9123 | 0.7879 | 0.9525 |
| 0.0612 | 3.0 | 186 | 0.1116 | 0.9858 | 0.7910 | 0.9298 | 0.6883 | 0.9587 |
| 0.0008 | 4.0 | 248 | 0.2774 | 0.9894 | 0.8108 | 0.7895 | 0.8333 | 0.8924 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
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