---
library_name: transformers
license: mit
base_model: pierreguillou/bert-base-cased-squad-v1.1-portuguese
tags:
- generated_from_trainer
model-index:
- name: ibama_29102024_20241029175942
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# ibama_29102024_20241029175942

This model is a fine-tuned version of [pierreguillou/bert-base-cased-squad-v1.1-portuguese](https://huggingface.co/pierreguillou/bert-base-cased-squad-v1.1-portuguese).

## Model description

Dataset com 1750 registros. 
Média do tamanho dos contextos: 2467.439831104856

["train"] : 1421 registros

["test"]  : 329 registros

{'exact_match': 6.990881458966565, 'f1': 41.36428322707063}



## Resultados: 

### :: Filtrando registros de ['test'] onde o contexto possuia até 6697 caracteres.
    
Modelo: ibama_29102024_20241029175942 : 

    'exact_match': 3.9755351681957185, 'f1': 38.429269059347

Modelo: pierreguillou/bert-base-cased-squad-v1.1-portuguese : 

    'exact_match': 6.422018348623853, 'f1': 37.47550481021018

Modelo: neuralmind/bert-base-portuguese-cased : 

    'exact_match': 0.0, 'f1': 21.520346204352514

### :: Filtrando registros de ['test'] onde o contexto possuia até 512 caracteres.

Modelo: ibama_29102024_20241029175942 : 

    'exact_match': 12.67605633802817, 'f1': 70.76635146201694 

Modelo: pierreguillou/bert-base-cased-squad-v1.1-portuguese : 

    'exact_match': 1.408450704225352, 'f1': 38.42469128241023

Modelo: neuralmind/bert-base-portuguese-cased : 
    
    'exact_match': 0.0, 'f1': 15.264048430063177

### Training results

It achieves the following results on the evaluation set:

- Loss: 4.1817

Epoch	Training Loss	Validation Loss
    1	No log	          4.598662
    2	No log	          4.266841
    3	No log	          4.225364
    4	No log	          4.181730

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1

### Notebook
https://colab.research.google.com/drive/1q1tZ7qkcjsNYrt3VLbrJ6C72mZihFzGm