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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_175
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_175
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: 0.4623
- Accuracy: 0.8937
- 1-f1: 0.4130
- 1-recall: 0.95
- 1-precision: 0.2639
- Balanced Acc: 0.9207
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0302 | 1.0 | 6 | 0.3907 | 0.8819 | 0.3878 | 0.95 | 0.2436 | 0.9145 |
| 0.0464 | 2.0 | 12 | 0.3874 | 0.9016 | 0.4186 | 0.9 | 0.2727 | 0.9008 |
| 0.0545 | 3.0 | 18 | 0.3953 | 0.8878 | 0.4000 | 0.95 | 0.2533 | 0.9176 |
| 0.0115 | 4.0 | 24 | 0.3764 | 0.9075 | 0.4471 | 0.95 | 0.2923 | 0.9279 |
| 0.0073 | 5.0 | 30 | 0.4056 | 0.9016 | 0.4318 | 0.95 | 0.2794 | 0.9248 |
| 0.0023 | 6.0 | 36 | 0.4623 | 0.8937 | 0.4130 | 0.95 | 0.2639 | 0.9207 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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