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# tmp_exs_faquad

This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the [FaQuAD dataset](https://huggingface.co/datasets/eraldoluis/faquad).

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

The model was trained on the `train` split and evaluated on the `eval` split.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

{"language": "pt", "license": "apache-2.0", "library_name": "transformers", "tags": ["extractive-qa"], "datasets": ["eraldoluis/faquad"], "metrics": ["squad"], "base_model": "neuralmind/bert-base-portuguese-cased", "model-index": [{"name": "faquad-bert-base-portuguese-cased", "results": [{"task": {"type": "extractive-qa", "name": "Extractive Question-Answering"}, "dataset": {"name": "FaQuAD", "type": "eraldoluis/faquad", "split": "eval"}, "metrics": [{"type": "f1", "value": 83.0912959832023, "name": "Eval F1 score (squad metric)", "verified": false}, {"type": "exact_match", "value": 74.53169347209082, "name": "Eval ExactMatch score (squad metric)", "verified": false}]}]}]}
transformers pytorch safetensors bert question-answering extractive-qa pt dataset:eraldoluis/faquad base_model:neuralmind/bert-base-portuguese-cased license:apache-2.0 model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #bert #question-answering #extractive-qa #pt #dataset-eraldoluis/faquad #base_model-neuralmind/bert-base-portuguese-cased #license-apache-2.0 #model-index #endpoints_compatible #region-us 




# tmp_exs_faquad

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the FaQuAD dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

The model was trained on the 'train' split and evaluated on the 'eval' split.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1

# tmp_exs_faquad

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the FaQuAD dataset. ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

The model was trained on the 'train' split and evaluated on the 'eval' split. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #safetensors #bert #question-answering #extractive-qa #pt #dataset-eraldoluis/faquad #base_model-neuralmind/bert-base-portuguese-cased #license-apache-2.0 #model-index #endpoints_compatible #region-us 
 # tmp_exs_faquad

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the FaQuAD dataset. ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

The model was trained on the 'train' split and evaluated on the 'eval' split. ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #safetensors #bert #question-answering #extractive-qa #pt #dataset-eraldoluis/faquad #base_model-neuralmind/bert-base-portuguese-cased #license-apache-2.0 #model-index #endpoints_compatible #region-us 
# tmp_exs_faquad

This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the FaQuAD dataset.## Model description

More information needed## Intended uses & limitations

More information needed## Training and evaluation data

The model was trained on the 'train' split and evaluated on the 'eval' split.## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1