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---
license: mit
base_model: neuralmind/bert-base-portuguese-cased
tags:
- generated_from_trainer
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: 1.1746
- Precision: 0.7707
- Recall: 0.7707
- F1: 0.7707
- Accuracy: 0.7707
## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5246 | 1.0 | 284 | 0.4708 | 0.7707 | 0.7707 | 0.7707 | 0.7707 |
| 0.394 | 2.0 | 568 | 0.4454 | 0.7919 | 0.7919 | 0.7919 | 0.7919 |
| 0.2585 | 3.0 | 852 | 0.8828 | 0.7407 | 0.7407 | 0.7407 | 0.7407 |
| 0.153 | 4.0 | 1136 | 1.1051 | 0.7372 | 0.7372 | 0.7372 | 0.7372 |
| 0.0935 | 5.0 | 1420 | 1.1746 | 0.7707 | 0.7707 | 0.7707 | 0.7707 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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