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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_143
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_143
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: 0.9495
- Accuracy: 0.8111
- 1-f1: 0.3077
- 1-recall: 0.7857
- 1-precision: 0.1913
- Balanced Acc: 0.7991
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0658 | 1.0 | 7 | 0.8253 | 0.8015 | 0.3067 | 0.8214 | 0.1885 | 0.8109 |
| 0.0629 | 2.0 | 14 | 0.8040 | 0.9008 | 0.3953 | 0.6071 | 0.2931 | 0.7622 |
| 0.0585 | 3.0 | 21 | 0.8857 | 0.7786 | 0.2927 | 0.8571 | 0.1765 | 0.8157 |
| 0.0308 | 4.0 | 28 | 0.7675 | 0.8760 | 0.3810 | 0.7143 | 0.2597 | 0.7997 |
| 0.0235 | 5.0 | 35 | 1.0302 | 0.7634 | 0.2791 | 0.8571 | 0.1667 | 0.8076 |
| 0.0016 | 6.0 | 42 | 0.9495 | 0.8111 | 0.3077 | 0.7857 | 0.1913 | 0.7991 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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