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---
license: mit
base_model: neuralmind/bert-large-portuguese-cased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- recall
- precision
model-index:
- name: final
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. -->
# final
This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3507
- Accuracy: 0.8945
- F1: 0.8863
- Recall: 0.8760
- Precision: 0.8968
## 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: 64
- eval_batch_size: 64
- seed: 5151
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|
| 0.485 | 0.9756 | 80 | 0.3916 | 0.8182 | 0.7984 | 0.7674 | 0.8319 |
| 0.3395 | 1.9512 | 160 | 0.3039 | 0.8764 | 0.8547 | 0.7752 | 0.9524 |
| 0.2139 | 2.9268 | 240 | 0.3122 | 0.8691 | 0.8548 | 0.8217 | 0.8908 |
| 0.084 | 3.9024 | 320 | 0.3507 | 0.8945 | 0.8863 | 0.8760 | 0.8968 |
| 0.058 | 4.8780 | 400 | 0.5087 | 0.8727 | 0.8571 | 0.8140 | 0.9052 |
| 0.0389 | 5.8537 | 480 | 0.4579 | 0.8982 | 0.888 | 0.8605 | 0.9174 |
| 0.0264 | 6.8293 | 560 | 0.5052 | 0.8873 | 0.8765 | 0.8527 | 0.9016 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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