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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_005
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_005
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: 0.7641
- Accuracy: 0.8038
- 1-f1: 0.2407
- 1-recall: 0.8667
- 1-precision: 0.1398
- Balanced Acc: 0.8341
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7419 | 1.0 | 7 | 0.8603 | 0.7010 | 0.1830 | 0.9333 | 0.1014 | 0.8128 |
| 0.0843 | 2.0 | 14 | 0.8453 | 0.7105 | 0.1769 | 0.8667 | 0.0985 | 0.7857 |
| 0.0276 | 3.0 | 21 | 0.5774 | 0.8086 | 0.2308 | 0.8 | 0.1348 | 0.8045 |
| 0.033 | 4.0 | 28 | 0.9772 | 0.7416 | 0.1940 | 0.8667 | 0.1092 | 0.8018 |
| 0.0304 | 5.0 | 35 | 0.7641 | 0.8038 | 0.2407 | 0.8667 | 0.1398 | 0.8341 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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