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# rob-base-superqa

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.

## Model description

More information needed

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad_v2", "quoref", "adversarial_qa", "duorc"], "task": ["question-answering"], "model-index": [{"name": "rob-base-superqa", "results": [{"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "adversarial_qa", "type": "adversarial_qa", "config": "adversarialQA", "split": "validation"}, "metrics": [{"type": "exact_match", "value": 43.8667, "name": "Exact Match", "verified": true}, {"type": "f1", "value": 55.135, "name": "F1", "verified": true}]}, {"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "squad_v2", "type": "squad_v2", "config": "squad_v2", "split": "validation"}, "metrics": [{"type": "exact_match", "value": 79.2432, "name": "Exact Match", "verified": true}, {"type": "f1", "value": 82.336, "name": "F1", "verified": true}]}, {"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "quoref", "type": "quoref", "config": "default", "split": "validation"}, "metrics": [{"type": "exact_match", "value": 78.8581, "name": "Exact Match", "verified": true}, {"type": "f1", "value": 82.8261, "name": "F1", "verified": true}]}]}]}
transformers pytorch tensorboard optimum_habana roberta question-answering generated_from_trainer dataset:squad_v2 dataset:quoref dataset:adversarial_qa dataset:duorc license:mit model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #optimum_habana #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #dataset-quoref #dataset-adversarial_qa #dataset-duorc #license-mit #model-index #endpoints_compatible #region-us 




# rob-base-superqa

This model is a fine-tuned version of roberta-base on the None dataset.

## Model description

More information needed

## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1

# rob-base-superqa

This model is a fine-tuned version of roberta-base on the None dataset. ## Model description

More information needed ## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #tensorboard #optimum_habana #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #dataset-quoref #dataset-adversarial_qa #dataset-duorc #license-mit #model-index #endpoints_compatible #region-us 
 # rob-base-superqa

This model is a fine-tuned version of roberta-base on the None dataset. ## Model description

More information needed ## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #tensorboard #optimum_habana #roberta #question-answering #generated_from_trainer #dataset-squad_v2 #dataset-quoref #dataset-adversarial_qa #dataset-duorc #license-mit #model-index #endpoints_compatible #region-us 
# rob-base-superqa

This model is a fine-tuned version of roberta-base on the None dataset.## Model description

More information needed## 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: 7e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.21.1
- Pytorch 1.11.0a0+gita4c10ee
- Datasets 2.4.0
- Tokenizers 0.12.1