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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_bsample_138
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_138
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: 0.5076
- Accuracy: 0.8343
- 1-f1: 0.3789
- 1-recall: 0.9
- 1-precision: 0.24
- Balanced Acc: 0.8652
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0366 | 1.0 | 6 | 0.5463 | 0.8904 | 0.4000 | 0.65 | 0.2889 | 0.7774 |
| 0.0454 | 2.0 | 12 | 0.5197 | 0.8483 | 0.4130 | 0.95 | 0.2639 | 0.8961 |
| 0.0517 | 3.0 | 18 | 0.7069 | 0.7697 | 0.3279 | 1.0 | 0.1961 | 0.8780 |
| 0.0401 | 4.0 | 24 | 0.4762 | 0.8343 | 0.3918 | 0.95 | 0.2468 | 0.8887 |
| 0.0222 | 5.0 | 30 | 0.6352 | 0.7921 | 0.3393 | 0.95 | 0.2065 | 0.8664 |
| 0.005 | 6.0 | 36 | 0.5076 | 0.8343 | 0.3789 | 0.9 | 0.24 | 0.8652 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3