---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
datasets:
- squad_v2
model-index:
- name: roberta-base-finetuned-squad
  results: 
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: squad_v2
      type: squad_v2
      config: squad_v2
      split: validation
    metrics:
    - type: exact_match
      value: 83.159
      name: Exact Match
    - type: f1
      value: 79.684
      name: F1
language:
- en
metrics:
- exact_match
- f1
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-base-finetuned-squad_v2

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the [SQuAD2.0](https://huggingface.co/datasets/squad_v2).
It achieves the following results on the evaluation set:
- Loss: 1.2340
- Exact Match: 79.684
- F1-score: 83.159

## Overview
**Language model:** roberta-base
**Language:** English  
**Downstream-task:** Extractive QA  
**Training data:** SQuAD 2.0  
**Eval data:** SQuAD 2.0  

## Training procedure

### 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: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.8978        | 1.0   | 8239  | 0.8532          |
| 0.6621        | 2.0   | 16478 | 0.9733          |
| 0.5045        | 3.0   | 24717 | 0.9010          |
| 0.3837        | 4.0   | 32956 | 1.0523          |
| 0.3069        | 5.0   | 41195 | 1.2340          |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.12.1
- Datasets 2.14.5
- Tokenizers 0.14.1