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---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_multilingual_roberta_base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_236
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_236
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_roberta_base](https://huggingface.co/AnonymousCS/populism_multilingual_roberta_base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2432
- Accuracy: 0.2393
- 1-f1: 0.072
- 1-recall: 1.0
- 1-precision: 0.0373
- Balanced Acc: 0.6081
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2483 | 1.0 | 4 | 1.9076 | 0.3180 | 0.0631 | 0.7778 | 0.0329 | 0.5409 |
| 0.8056 | 2.0 | 8 | 1.1576 | 0.5770 | 0.0851 | 0.6667 | 0.0455 | 0.6205 |
| 0.592 | 3.0 | 12 | 1.8927 | 0.3541 | 0.0664 | 0.7778 | 0.0347 | 0.5595 |
| 0.3242 | 4.0 | 16 | 2.2432 | 0.2393 | 0.072 | 1.0 | 0.0373 | 0.6081 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3