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library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_034
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_034
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7421
- Accuracy: 0.7949
- 1-f1: 0.3540
- 1-recall: 1.0
- 1-precision: 0.2151
- Balanced Acc: 0.8914
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0452 | 1.0 | 6 | 0.5724 | 0.7640 | 0.3226 | 1.0 | 0.1923 | 0.875 |
| 0.0251 | 2.0 | 12 | 0.6141 | 0.7809 | 0.3390 | 1.0 | 0.2041 | 0.8839 |
| 0.0333 | 3.0 | 18 | 0.5585 | 0.8146 | 0.3654 | 0.95 | 0.2262 | 0.8783 |
| 0.0148 | 4.0 | 24 | 0.6092 | 0.7865 | 0.3333 | 0.95 | 0.2021 | 0.8634 |
| 0.009 | 5.0 | 30 | 0.5340 | 0.8455 | 0.4086 | 0.95 | 0.2603 | 0.8946 |
| 0.0044 | 6.0 | 36 | 0.6464 | 0.8062 | 0.3551 | 0.95 | 0.2184 | 0.8738 |
| 0.0035 | 7.0 | 42 | 0.7421 | 0.7949 | 0.3540 | 1.0 | 0.2151 | 0.8914 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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