Instructions to use lfcc/bert-portuguese-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lfcc/bert-portuguese-squad2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="lfcc/bert-portuguese-squad2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("lfcc/bert-portuguese-squad2") model = AutoModelForQuestionAnswering.from_pretrained("lfcc/bert-portuguese-squad2") - Notebooks
- Google Colab
- Kaggle
bert-portuguese-squad2
This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on SQuAD_v2 dataset, translated for portuguese.
Model description
More information needed
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: 3
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0+cu117
- Datasets 2.6.1
- Tokenizers 0.13.2
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