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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_bsample_011
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_bsample_011
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: 0.5113
- Accuracy: 0.8566
- 1-f1: 0.4317
- 1-recall: 0.9375
- 1-precision: 0.2804
- Balanced Acc: 0.8946
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0711 | 1.0 | 6 | 0.4762 | 0.9002 | 0.4554 | 0.7188 | 0.3333 | 0.8151 |
| 0.0826 | 2.0 | 12 | 0.4962 | 0.9020 | 0.4490 | 0.6875 | 0.3333 | 0.8014 |
| 0.029 | 3.0 | 18 | 0.4481 | 0.8530 | 0.4336 | 0.9688 | 0.2793 | 0.9073 |
| 0.0267 | 4.0 | 24 | 0.3742 | 0.8893 | 0.4404 | 0.75 | 0.3117 | 0.8239 |
| 0.0054 | 5.0 | 30 | 0.4741 | 0.8548 | 0.4286 | 0.9375 | 0.2778 | 0.8936 |
| 0.0072 | 6.0 | 36 | 0.5113 | 0.8566 | 0.4317 | 0.9375 | 0.2804 | 0.8946 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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