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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_181
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_181
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_uncased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_uncased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8742
- Accuracy: 0.8427
- 1-f1: 0.3355
- 1-recall: 0.7027
- 1-precision: 0.2203
- Balanced Acc: 0.7769
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.1663 | 1.0 | 9 | 1.0609 | 0.7435 | 0.2632 | 0.8108 | 0.1571 | 0.7751 |
| 0.2964 | 2.0 | 18 | 0.7859 | 0.8061 | 0.3060 | 0.7568 | 0.1918 | 0.7829 |
| 0.0629 | 3.0 | 27 | 0.7313 | 0.7695 | 0.2911 | 0.8378 | 0.1761 | 0.8016 |
| 0.0174 | 4.0 | 36 | 0.7297 | 0.8336 | 0.3313 | 0.7297 | 0.2143 | 0.7848 |
| 0.0657 | 5.0 | 45 | 0.9259 | 0.7893 | 0.31 | 0.8378 | 0.1902 | 0.8121 |
| 0.0357 | 6.0 | 54 | 0.8742 | 0.8427 | 0.3355 | 0.7027 | 0.2203 | 0.7769 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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