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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) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1817
## 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 com testes filtrando registros com contexto at茅 6697 caracteres
content/sample_data/ibama_29102024_20241029175942 :
'exact_match': 3.9755351681957185, 'f1': 38.429269059347
pierreguillou/bert-base-cased-squad-v1.1-portuguese :
'exact_match': 6.422018348623853, 'f1': 37.47550481021018
neuralmind/bert-base-portuguese-cased :
'exact_match': 0.0, 'f1': 21.520346204352514
## Resultados com testes filtrando registros com contexto at茅 512 caracteres
content/sample_data/ibama_29102024_20241029175942 :
'exact_match': 12.67605633802817, 'f1': 70.76635146201694
pierreguillou/bert-base-cased-squad-v1.1-portuguese :
'exact_match': 1.408450704225352, 'f1': 38.42469128241023
neuralmind/bert-base-portuguese-cased :
'exact_match': 0.0, 'f1': 15.264048430063177
## 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: 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
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 1.0 | 45 | 4.5987 |
| No log | 2.0 | 90 | 4.2668 |
| No log | 3.0 | 135 | 4.2254 |
| No log | 4.0 | 180 | 4.1817 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
|