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_model23
results: []
populism_model23
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: 0.4182
- Accuracy: 0.8892
- F1: 0.3088
- Recall: 0.6562
- Precision: 0.2019
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 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 27 | 0.4190 | 0.9080 | 0.3390 | 0.625 | 0.2326 |
| 0.4132 | 2.0 | 54 | 0.4420 | 0.9292 | 0.3617 | 0.5312 | 0.2742 |
| 0.4132 | 3.0 | 81 | 0.3853 | 0.8738 | 0.3007 | 0.7188 | 0.1901 |
| 0.2662 | 4.0 | 108 | 0.4240 | 0.9080 | 0.3276 | 0.5938 | 0.2262 |
| 0.2662 | 5.0 | 135 | 0.4182 | 0.8892 | 0.3088 | 0.6562 | 0.2019 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0