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_model11
results: []
populism_model11
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: 0.3482
- Accuracy: 0.9351
- F1: 0.4706
- Recall: 0.6316
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 |
|---|---|---|---|---|---|---|
| No log | 1.0 | 13 | 0.3782 | 0.9471 | 0.5 | 0.5789 |
| No log | 2.0 | 26 | 0.3140 | 0.9327 | 0.4815 | 0.6842 |
| No log | 3.0 | 39 | 0.3231 | 0.9327 | 0.4615 | 0.6316 |
| 0.3033 | 4.0 | 52 | 0.3983 | 0.9495 | 0.5116 | 0.5789 |
| 0.3033 | 5.0 | 65 | 0.3482 | 0.9351 | 0.4706 | 0.6316 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0