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---
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
should probably proofread and complete it, then remove this comment. -->
# 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.
M茅dia 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 at茅 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 at茅 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 |