|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: neuralmind/bert-base-portuguese-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- recall |
|
- precision |
|
model-index: |
|
- name: neuralmind/bert-base-portuguese-cased |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# neuralmind/bert-base-portuguese-cased |
|
|
|
This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0500 |
|
- Accuracy: 0.7415 |
|
- F1: 0.6919 |
|
- Recall: 0.7472 |
|
- Precision: 0.6838 |
|
|
|
## 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: 5151 |
|
- 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 |
|
- lr_scheduler_warmup_steps: 150 |
|
- num_epochs: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
|
| 0.0667 | 1.0 | 18 | 0.0661 | 0.5536 | 0.4531 | 0.4520 | 0.4571 | |
|
| 0.0624 | 2.0 | 36 | 0.0646 | 0.6696 | 0.5743 | 0.5752 | 0.5736 | |
|
| 0.0625 | 3.0 | 54 | 0.0628 | 0.7321 | 0.6510 | 0.6510 | 0.6510 | |
|
| 0.0612 | 4.0 | 72 | 0.0603 | 0.7411 | 0.6733 | 0.6795 | 0.6687 | |
|
| 0.0566 | 5.0 | 90 | 0.0568 | 0.7768 | 0.7184 | 0.7260 | 0.7125 | |
|
| 0.0544 | 6.0 | 108 | 0.0530 | 0.7589 | 0.7216 | 0.7588 | 0.7119 | |
|
| 0.0488 | 7.0 | 126 | 0.0497 | 0.8214 | 0.7812 | 0.8010 | 0.7688 | |
|
| 0.0398 | 8.0 | 144 | 0.0498 | 0.7946 | 0.7629 | 0.8054 | 0.75 | |
|
| 0.0276 | 9.0 | 162 | 0.0540 | 0.8125 | 0.7681 | 0.7838 | 0.7575 | |
|
| 0.0184 | 10.0 | 180 | 0.0674 | 0.7679 | 0.7156 | 0.7312 | 0.7065 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.47.0 |
|
- Pytorch 2.5.1+cu121 |
|
- Datasets 3.2.0 |
|
- Tokenizers 0.21.0 |
|
|
