metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: populism_model2
results: []
populism_model2
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4895
- Accuracy: 0.9149
- F1: 0.4051
- Recall: 0.5479
- Precision: 0.3213
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 | Precision |
|---|---|---|---|---|---|---|---|
| 0.6178 | 1.0 | 87 | 0.4434 | 0.7889 | 0.2829 | 0.7877 | 0.1724 |
| 0.4174 | 2.0 | 174 | 0.4149 | 0.7589 | 0.2885 | 0.9247 | 0.1709 |
| 0.3132 | 3.0 | 261 | 0.4303 | 0.9008 | 0.3744 | 0.5616 | 0.2808 |
| 0.2642 | 4.0 | 348 | 0.4344 | 0.9015 | 0.4138 | 0.6575 | 0.3019 |
| 0.2153 | 5.0 | 435 | 0.4895 | 0.9149 | 0.4051 | 0.5479 | 0.3213 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0