---
license: mit
tags:
- generated_from_trainer
datasets:
- squad_v2
- quoref
- adversarial_qa
- duorc
model-index:
- name: rob-base-superqa2
  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: 79.2365
      name: Exact Match
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmUxNmNjZTg2YzcxMTBkYjE4YTVmODM3YWY2NTFkMmY3NWNiMGYyZTkxZDlkMTJiMjBkZjVhY2NlMGRjYzAyMCIsInZlcnNpb24iOjF9.dn0e2EJ8ImOWODCoRH_d7v10vtxv2ZfRkeWKF-R62sz2ufMjyC9brQihULMw5ZhnSQq5bBFFvauhG6KpLgzgDA
    - type: f1
      value: 82.3326
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYWQyZGNhY2Y3OWE5MTg0ZDM4MmQ0NDk5MjRmODA2OTVmY2ExYTc1MjM2ZTcyNzUxMGI2OWIwMzY5NzMzNzU3NyIsInZlcnNpb24iOjF9.j2Y2sfHayDV5Qfka1bVSbkBIAyMa-rpUxMNICTFvsDVTCnzRPkNVrtrE9dBiDKQa2vVOZNiKrbJEDfXE1xOIBQ
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: adversarial_qa
      type: adversarial_qa
      config: adversarialQA
      split: test
    metrics:
    - type: exact_match
      value: 12.4
      name: Exact Match
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDExM2Q2NjIxODU4N2FiOWY3NjVjZjNmNzYwYWNhODllMzQxZGVkMzZlMWUzMzJhYTQwMDZhMGQyZjZjNWMyNiIsInZlcnNpb24iOjF9.rMzb2Cna0y3MljrLCRZ8r8SwPFTtwr4OG1mD6gdn3zcVgqX3Td0Q04n_O7RoGuH1788xqEvdeGltd-_TRrC0Aw
    - type: f1
      value: 12.4
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTNlYjgzMzZlNmYzNjkyYjg4MzYxNTZjZjNkYzA0NTZmNjk5MjI5YzM5YWQ0Y2VlMjVkYWIxNTk2YWJkMTQzYyIsInZlcnNpb24iOjF9.Du89uCtL2-mlV-tewIVKqwG9O53JE3B4Jflpzv4nptpa0MtYiGUAMCunMuWRdBXMe_YdqKDjr7_alJ0-XNRVDQ
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: adversarial_qa
      type: adversarial_qa
      config: adversarialQA
      split: validation
    metrics:
    - type: exact_match
      value: 42.3667
      name: Exact Match
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNmJmYmU5OGFmNjBjNzM1YmRhNDViNDI3MTMwZjg2N2EwYmM2ZDkyZmI4MmY5OGE4NmU5YTA1NThjZDdkYjkyYyIsInZlcnNpb24iOjF9.Iah8AxkCHsDHRTK8SLXzo4qd0C3Ku7bqGVJIJHiPxC2VO3bfz6c5emSSVZk5fACbKYMFoKTeLr6_XTwfTNjGAg
    - type: f1
      value: 53.3255
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYmVlMGFiNjhhOWVjZWUzZTkwOWYzNWQzNjVhNzFhMjRkOGRmNmYwNWIyN2VmZWQ0MDZlNzk0NWM5MzgxMzdhYyIsInZlcnNpb24iOjF9._lW0JTSbvQ-pUBG0cZwpKzCvXMXmjcLrAaxk-bhou_Hf5R3Sw4AEAEy0Vx5qvxk3e30E73mYTInrtBqH8JA3BQ
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: squad
      type: squad
      config: plain_text
      split: validation
    metrics:
    - type: exact_match
      value: 86.1925
      name: Exact Match
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOWMxYmE4MWRjZDRlMWY3NWMxMjI0YTI5MmVkZTI5OGZiNzM2ZWMyNzlhOGRlNjMzZTBmYWM2OGU0MWM1NDc0MiIsInZlcnNpb24iOjF9.3h6zsLHiqX9ScqvvKhirv4n3S2bP1qpAmnGQrz2eoY0vps2UAN4afyXA_PLMlbk_osgN8Wvnefx74VIgELh6DQ
    - type: f1
      value: 92.4306
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMTVhMWIzYWJhMWNkNzg5NDNlZTdmY2UwNDM3ZWIzZmZjNTA5NDNiMjk2NjI0MTVmNDRjOTYyYjU0YWNmYWE4ZSIsInZlcnNpb24iOjF9.pMkm1BJU1PAsWruRIWhNFrF4DD-nXaE5Gq6sR5mZfQUoeESNWiYGU2GppAvnIEVah0PmdRQHd-DBRK0hDJ2PBg
---

<!-- 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. -->

# rob-base-superqa2

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: 0.0001
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

### Training results



### Framework versions

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