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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_001
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_001
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: 0.6048
- Accuracy: 0.8258
- 1-f1: 0.3283
- 1-recall: 0.8917
- 1-precision: 0.2012
- Balanced Acc: 0.8571
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1791 | 1.0 | 167 | 1.0272 | 0.5191 | 0.1644 | 0.9910 | 0.0896 | 0.7432 |
| 0.1099 | 2.0 | 334 | 0.7126 | 0.6653 | 0.2174 | 0.9744 | 0.1224 | 0.8121 |
| 0.1254 | 3.0 | 501 | 0.7505 | 0.7070 | 0.2393 | 0.9654 | 0.1366 | 0.8298 |
| 0.1196 | 4.0 | 668 | 0.5164 | 0.8148 | 0.3148 | 0.8917 | 0.1912 | 0.8513 |
| 0.056 | 5.0 | 835 | 0.5215 | 0.8677 | 0.3716 | 0.8195 | 0.2403 | 0.8448 |
| 0.0547 | 6.0 | 1002 | 0.6048 | 0.8258 | 0.3283 | 0.8917 | 0.2012 | 0.8571 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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