metadata
library_name: transformers
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: BingoGuard-bert-large-pt
results: []
BingoGuard-bert-large-pt
This model is a fine-tuned version of neuralmind/bert-large-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1290
- Accuracy: 0.9517
- F1: 0.7135
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.3873 | 1.0 | 1823 | 0.1427 | 0.9344 | 0.6598 |
| 0.3097 | 2.0 | 3646 | 0.1137 | 0.9457 | 0.6839 |
| 0.2555 | 3.0 | 5469 | 0.1281 | 0.9383 | 0.6736 |
| 0.2167 | 4.0 | 7292 | 0.1229 | 0.9507 | 0.7191 |
| 0.1873 | 4.9975 | 9110 | 0.1290 | 0.9517 | 0.7135 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4