metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_016
results: []
populism_classifier_016
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: 0.5712
- Accuracy: 0.9208
- 1-f1: 0.5333
- 1-recall: 0.5455
- 1-precision: 0.5217
- Balanced Acc: 0.7501
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 OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|---|---|---|---|
| 0.3101 | 1.0 | 9 | 0.2765 | 0.8491 | 0.5122 | 0.9545 | 0.35 | 0.8970 |
| 0.2425 | 2.0 | 18 | 0.3022 | 0.8981 | 0.5424 | 0.7273 | 0.4324 | 0.8204 |
| 0.1839 | 3.0 | 27 | 0.5712 | 0.9208 | 0.5333 | 0.5455 | 0.5217 | 0.7501 |
Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4