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_model6
results: []
populism_model6
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: 0.3099
- Accuracy: 0.9255
- F1: 0.6389
- Recall: 0.8214
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 | 22 | 0.2588 | 0.8481 | 0.5138 | 1.0 |
| No log | 2.0 | 44 | 0.2545 | 0.9112 | 0.6173 | 0.8929 |
| 0.3326 | 3.0 | 66 | 0.3131 | 0.9169 | 0.5915 | 0.75 |
| 0.3326 | 4.0 | 88 | 0.3138 | 0.9198 | 0.6 | 0.75 |
| 0.2053 | 5.0 | 110 | 0.3099 | 0.9255 | 0.6389 | 0.8214 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0