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_model83
results: []
populism_model83
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: 0.0991
- Accuracy: 0.9653
- F1: 0.7
- Recall: 0.9545
- Precision: 0.5526
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 | 17 | 0.1368 | 0.9672 | 0.7119 | 0.9545 | 0.5676 |
| No log | 2.0 | 34 | 0.1096 | 0.9479 | 0.6197 | 1.0 | 0.4490 |
| 0.2204 | 3.0 | 51 | 0.1206 | 0.9363 | 0.5714 | 1.0 | 0.4 |
| 0.2204 | 4.0 | 68 | 0.0942 | 0.9633 | 0.6885 | 0.9545 | 0.5385 |
| 0.2204 | 5.0 | 85 | 0.0991 | 0.9653 | 0.7 | 0.9545 | 0.5526 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0