metadata
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- accuracy
- f1
model-index:
- name: oracle_class_bin
results: []
oracle_class_bin
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1746
- Precision: 0.8254
- Recall: 0.7923
- Accuracy: 0.9615
- F1: 0.8085
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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 |
|---|---|---|---|---|---|---|---|
| 0.1271 | 0.8407 | 1800 | 0.1045 | 0.7513 | 0.8544 | 0.9560 | 0.7996 |
| 0.0913 | 1.6815 | 3600 | 0.1075 | 0.8110 | 0.7968 | 0.9601 | 0.8038 |
| 0.0791 | 2.5222 | 5400 | 0.1283 | 0.8287 | 0.7885 | 0.9615 | 0.8081 |
| 0.0553 | 3.3629 | 7200 | 0.1272 | 0.8160 | 0.8067 | 0.9615 | 0.8113 |
| 0.0384 | 4.2036 | 9000 | 0.1746 | 0.8254 | 0.7923 | 0.9615 | 0.8085 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.0
- Datasets 2.20.0
- Tokenizers 0.19.1