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---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
model-index:
- name: populism_model15
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_model15
This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4110
- Accuracy: 0.8678
- F1: 0.4286
- Recall: 0.6207
## 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|
| No log | 1.0 | 12 | 0.3550 | 0.7934 | 0.4186 | 0.9310 |
| No log | 2.0 | 24 | 0.3812 | 0.8512 | 0.4 | 0.6207 |
| No log | 3.0 | 36 | 0.4112 | 0.8512 | 0.4 | 0.6207 |
| No log | 4.0 | 48 | 0.4371 | 0.8705 | 0.4337 | 0.6207 |
| 0.3577 | 5.0 | 60 | 0.4110 | 0.8678 | 0.4286 | 0.6207 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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