---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_uncased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: antielite_classifier_all
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# antielite_classifier_all

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: 0.7651
- Accuracy: 0.9293
- 1-f1: 0.6331
- 1-recall: 0.6543
- 1-precision: 0.6133
- Balanced Acc: 0.8060

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3031        | 1.0   | 871  | 0.3153          | 0.8819   | 0.5737 | 0.8522   | 0.4324      | 0.8686       |
| 0.2011        | 2.0   | 1742 | 0.3090          | 0.8848   | 0.5852 | 0.8714   | 0.4405      | 0.8788       |
| 0.1064        | 3.0   | 2613 | 0.5096          | 0.9195   | 0.6345 | 0.7498   | 0.5500      | 0.8434       |
| 0.0961        | 4.0   | 3484 | 0.7651          | 0.9293   | 0.6331 | 0.6543   | 0.6133      | 0.8060       |


### Framework versions

- Transformers 5.8.0.dev0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2