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# roberta-base-finetuned-squad-v1

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the squad dataset.

## Model description

Given a context / content, the model answers to a question by searching the content and extracting the relavant information.

## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

## Training results

- training loss: 0.77257

## Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
{"license": "mit", "tags": ["generated_from_trainer"], "base_model": "roberta-base", "model-index": [{"name": "roberta-base-finetuned-squad-v1", "results": [{"task": {"type": "question-answering", "name": "Question Answering"}, "dataset": {"name": "SQUAD", "type": "squad"}, "metrics": [{"type": "f1", "value": 92.296}, {"type": "exact_match", "value": 86.045}]}]}]}
transformers pytorch tensorboard safetensors roberta question-answering generated_from_trainer base_model:roberta-base license:mit model-index endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #question-answering #generated_from_trainer #base_model-roberta-base #license-mit #model-index #endpoints_compatible #region-us 




# roberta-base-finetuned-squad-v1

This model is a fine-tuned version of roberta-base on the squad dataset.

## Model description

Given a context / content, the model answers to a question by searching the content and extracting the relavant information.

## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

## Training results

- training loss: 0.77257

## Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
# roberta-base-finetuned-squad-v1

This model is a fine-tuned version of roberta-base on the squad dataset. ## Model description

Given a context / content, the model answers to a question by searching the content and extracting the relavant information. ## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP ## Training results

- training loss: 0.77257 ## Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #question-answering #generated_from_trainer #base_model-roberta-base #license-mit #model-index #endpoints_compatible #region-us 
 # roberta-base-finetuned-squad-v1

This model is a fine-tuned version of roberta-base on the squad dataset. ## Model description

Given a context / content, the model answers to a question by searching the content and extracting the relavant information. ## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP ## Training results

- training loss: 0.77257 ## Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #tensorboard #safetensors #roberta #question-answering #generated_from_trainer #base_model-roberta-base #license-mit #model-index #endpoints_compatible #region-us 
# roberta-base-finetuned-squad-v1

This model is a fine-tuned version of roberta-base on the squad dataset.## Model description

Given a context / content, the model answers to a question by searching the content and extracting the relavant information.## Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP## Training results

- training loss: 0.77257## Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3