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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_140
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_140
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: 0.6724
- Accuracy: 0.9764
- 1-f1: 0.5652
- 1-recall: 0.4483
- 1-precision: 0.7647
- Balanced Acc: 0.7217
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3592 | 1.0 | 27 | 0.2920 | 0.9776 | 0.6415 | 0.5862 | 0.7083 | 0.7888 |
| 0.442 | 2.0 | 54 | 0.2666 | 0.9717 | 0.5714 | 0.5517 | 0.5926 | 0.7691 |
| 0.1402 | 3.0 | 81 | 0.1793 | 0.9528 | 0.5455 | 0.8276 | 0.4068 | 0.8924 |
| 0.0193 | 4.0 | 108 | 0.3450 | 0.9717 | 0.6129 | 0.6552 | 0.5758 | 0.8190 |
| 0.051 | 5.0 | 135 | 0.6724 | 0.9764 | 0.5652 | 0.4483 | 0.7647 | 0.7217 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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