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library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_cased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_144
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_144
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2996
- Accuracy: 0.9904
- 1-f1: 0.8224
- 1-recall: 0.7719
- 1-precision: 0.88
- Balanced Acc: 0.8844
## 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 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3457 | 1.0 | 62 | 0.2102 | 0.9838 | 0.6981 | 0.6491 | 0.7551 | 0.8214 |
| 0.0606 | 2.0 | 124 | 0.2551 | 0.9868 | 0.7547 | 0.7018 | 0.8163 | 0.8485 |
| 0.0061 | 3.0 | 186 | 0.2000 | 0.9889 | 0.8070 | 0.8070 | 0.8070 | 0.9006 |
| 0.0005 | 4.0 | 248 | 0.2225 | 0.9924 | 0.8598 | 0.8070 | 0.92 | 0.9025 |
| 0.0016 | 5.0 | 310 | 0.1739 | 0.9889 | 0.8036 | 0.7895 | 0.8182 | 0.8921 |
| 0.057 | 6.0 | 372 | 0.3100 | 0.9919 | 0.8462 | 0.7719 | 0.9362 | 0.8852 |
| 0.1151 | 7.0 | 434 | 0.2996 | 0.9904 | 0.8224 | 0.7719 | 0.88 | 0.8844 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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