---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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