metadata
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_model306
results: []
populism_model306
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2810
- Accuracy: 0.9799
- 1-f1: 0.8571
- 1-recall: 0.7778
- 1-precision: 0.9545
- Balanced Acc: 0.8873
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 OptimizerNames.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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|---|---|---|---|---|---|---|---|---|
| 0.3232 | 1.0 | 44 | 0.3076 | 0.9713 | 0.8148 | 0.8148 | 0.8148 | 0.8996 |
| 0.1145 | 2.0 | 88 | 0.3175 | 0.9742 | 0.8085 | 0.7037 | 0.95 | 0.8503 |
| 0.0637 | 3.0 | 132 | 0.2810 | 0.9799 | 0.8571 | 0.7778 | 0.9545 | 0.8873 |
Framework versions
- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0