metadata
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_model9
results: []
populism_model9
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: 0.4821
- Accuracy: 0.9430
- F1: 0.4062
- Recall: 0.4483
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: 64
- eval_batch_size: 64
- 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 | 42 | 0.5072 | 0.9520 | 0.2 | 0.1379 |
| 0.4287 | 2.0 | 84 | 0.3206 | 0.8951 | 0.375 | 0.7241 |
| 0.3071 | 3.0 | 126 | 0.3293 | 0.9160 | 0.4167 | 0.6897 |
| 0.2561 | 4.0 | 168 | 0.5054 | 0.9400 | 0.3103 | 0.3103 |
| 0.2026 | 5.0 | 210 | 0.4821 | 0.9430 | 0.4062 | 0.4483 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0