File size: 2,369 Bytes
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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_052
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_052
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: 0.8004
- Accuracy: 0.7895
- 1-f1: 0.2895
- 1-recall: 0.8148
- 1-precision: 0.176
- Balanced Acc: 0.8014
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0336 | 1.0 | 8 | 0.7242 | 0.7719 | 0.2822 | 0.8519 | 0.1691 | 0.8097 |
| 0.0112 | 2.0 | 16 | 0.7139 | 0.7953 | 0.3137 | 0.8889 | 0.1905 | 0.8395 |
| 0.0513 | 3.0 | 24 | 1.1909 | 0.6257 | 0.2131 | 0.9630 | 0.1198 | 0.7850 |
| 0.0171 | 4.0 | 32 | 0.6467 | 0.8187 | 0.3212 | 0.8148 | 0.2 | 0.8169 |
| 0.0212 | 5.0 | 40 | 0.8381 | 0.7368 | 0.2623 | 0.8889 | 0.1538 | 0.8086 |
| 0.0151 | 6.0 | 48 | 0.8004 | 0.7895 | 0.2895 | 0.8148 | 0.176 | 0.8014 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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