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---
license: mit
tags:
- generated_from_trainer
base_model: neuralmind/bert-base-portuguese-cased
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: hate_BERTimbau_v1
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. -->
# hate_BERTimbau_v1
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: 1.1389
- Precision: 0.7715
- Recall: 0.7690
- F1: 0.7700
- Accuracy: 0.7690
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5196 | 1.0 | 284 | 0.4981 | 0.7509 | 0.7566 | 0.7482 | 0.7566 |
| 0.4019 | 2.0 | 568 | 0.4680 | 0.7923 | 0.7813 | 0.7843 | 0.7813 |
| 0.2706 | 3.0 | 852 | 0.6745 | 0.7525 | 0.7531 | 0.7355 | 0.7531 |
| 0.1601 | 4.0 | 1136 | 0.9990 | 0.7632 | 0.7672 | 0.7573 | 0.7672 |
| 0.0975 | 5.0 | 1420 | 1.1389 | 0.7715 | 0.7690 | 0.7700 | 0.7690 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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