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_model3
results: []
populism_model3
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: 0.6057
- Accuracy: 0.9272
- F1: 0.4842
- Recall: 0.5565
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 | 127 | 0.4054 | 0.8524 | 0.3817 | 0.7419 |
| No log | 2.0 | 254 | 0.3590 | 0.8341 | 0.3853 | 0.8468 |
| No log | 3.0 | 381 | 0.3850 | 0.8816 | 0.4429 | 0.7661 |
| 0.3487 | 4.0 | 508 | 0.6005 | 0.9302 | 0.4758 | 0.5161 |
| 0.3487 | 5.0 | 635 | 0.6057 | 0.9272 | 0.4842 | 0.5565 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0