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library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_036
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_036
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6998
- Accuracy: 0.8473
- 1-f1: 0.2400
- 1-recall: 0.84
- 1-precision: 0.14
- Balanced Acc: 0.8438
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0557 | 1.0 | 9 | 0.8331 | 0.7474 | 0.1852 | 1.0 | 0.1020 | 0.8700 |
| 0.0378 | 2.0 | 18 | 0.4860 | 0.8507 | 0.2697 | 0.96 | 0.1569 | 0.9038 |
| 0.0335 | 3.0 | 27 | 0.4809 | 0.9036 | 0.2881 | 0.68 | 0.1828 | 0.7951 |
| 0.0044 | 4.0 | 36 | 0.5310 | 0.9001 | 0.2810 | 0.68 | 0.1771 | 0.7933 |
| 0.0018 | 5.0 | 45 | 0.6998 | 0.8473 | 0.2400 | 0.84 | 0.14 | 0.8438 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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