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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_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_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: 0.4012
- Accuracy: 0.9320
- 1-f1: 0.4981
- 1-recall: 0.7068
- 1-precision: 0.3846
- Balanced Acc: 0.8250
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3001 | 1.0 | 436 | 0.3010 | 0.9048 | 0.4331 | 0.7624 | 0.3025 | 0.8372 |
| 0.2093 | 2.0 | 872 | 0.2855 | 0.8979 | 0.4278 | 0.8 | 0.2920 | 0.8514 |
| 0.0919 | 3.0 | 1308 | 0.3977 | 0.9390 | 0.4988 | 0.6361 | 0.4103 | 0.7951 |
| 0.0759 | 4.0 | 1744 | 0.4012 | 0.9320 | 0.4981 | 0.7068 | 0.3846 | 0.8250 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4
|