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_048
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_048
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: 0.6899
- Accuracy: 0.8010
- 1-f1: 0.2569
- 1-recall: 0.875
- 1-precision: 0.1505
- Balanced Acc: 0.8365
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0677 | 1.0 | 4 | 0.9887 | 0.7125 | 0.2148 | 1.0 | 0.1203 | 0.8504 |
| 0.1969 | 2.0 | 8 | 0.5845 | 0.8428 | 0.3043 | 0.875 | 0.1842 | 0.8582 |
| 0.0666 | 3.0 | 12 | 0.6913 | 0.7838 | 0.2542 | 0.9375 | 0.1471 | 0.8575 |
| 0.0131 | 4.0 | 16 | 0.5660 | 0.8477 | 0.2955 | 0.8125 | 0.1806 | 0.8308 |
| 0.0847 | 5.0 | 20 | 0.5668 | 0.8698 | 0.3117 | 0.75 | 0.1967 | 0.8123 |
| 0.0096 | 6.0 | 24 | 0.6899 | 0.8010 | 0.2569 | 0.875 | 0.1505 | 0.8365 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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