RichardErkhov/

deepset_-_roberta-base-squad2-distilled-8bits

• Model creator: https://huggingface.co/deepset/
• Original model: https://huggingface.co/deepset/roberta-base-squad2-distilled/

Original model description:

• exbert datasets:
• squad_v2 thumbnail: https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg model-index:
• name: deepset/roberta-base-squad2-distilled 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: 80.8593 name: Exact Match verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzVjNzkxNmNiNDkzNzdiYjJjZGM3ZTViMGJhOGM2ZjFmYjg1MjYxMDM2YzM5NWMwNDIyYzNlN2QwNGYyNDMzZSIsInZlcnNpb24iOjF9.Rgww8tf8D7nF2dh2U_DMrFzmp87k8s7RFibrDXSvQyA66PGWXwjlsd1552lzjHnNV5hvHUM1-h3PTuY_5p64BA
    • type: f1 value: 84.0104 name: F1 verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTAyZDViNWYzNjA4OWQ5MzgyYmQ2ZDlhNWRhMTIzYTYxYzViMmI4NWE4ZGU5MzVhZTAwNTRlZmRlNWUwMjI0ZSIsInZlcnNpb24iOjF9.Er21BNgJ3jJXLuZtpubTYq9wCwO1i_VLQFwS5ET0e4eAYVVj0aOA40I5FvP5pZac3LjkCnVacxzsFWGCYVmnDA
  • task: type: question-answering name: Question Answering dataset: name: squad type: squad config: plain_text split: validation metrics:
    • type: exact_match value: 86.225 name: Exact Match
    • type: f1 value: 92.483 name: F1
  • task: type: question-answering name: Question Answering dataset: name: adversarial_qa type: adversarial_qa config: adversarialQA split: validation metrics:
    • type: exact_match value: 29.900 name: Exact Match
    • type: f1 value: 41.183 name: F1
  • task: type: question-answering name: Question Answering dataset: name: squad_adversarial type: squad_adversarial config: AddOneSent split: validation metrics:
    • type: exact_match value: 79.071 name: Exact Match
    • type: f1 value: 84.472 name: F1
  • task: type: question-answering name: Question Answering dataset: name: squadshifts amazon type: squadshifts config: amazon split: test metrics:
    • type: exact_match value: 70.733 name: Exact Match
    • type: f1 value: 83.958 name: F1
  • task: type: question-answering name: Question Answering dataset: name: squadshifts new_wiki type: squadshifts config: new_wiki split: test metrics:
    • type: exact_match value: 82.011 name: Exact Match
    • type: f1 value: 91.092 name: F1
  • task: type: question-answering name: Question Answering dataset: name: squadshifts nyt type: squadshifts config: nyt split: test metrics:
    • type: exact_match value: 84.203 name: Exact Match
    • type: f1 value: 91.521 name: F1
  • task: type: question-answering name: Question Answering dataset: name: squadshifts reddit type: squadshifts config: reddit split: test metrics:
    • type: exact_match value: 72.029 name: Exact Match
    • type: f1 value: 83.454 name: F1

Overview

Details

• haystack's distillation feature was used for training. deepset/roberta-large-squad2 was used as the teacher model.

Hyperparameters

batch_size = 80
n_epochs = 4
max_seq_len = 384
learning_rate = 3e-5
lr_schedule = LinearWarmup
embeds_dropout_prob = 0.1
temperature = 1.5
distillation_loss_weight = 0.75

Performance

"exact": 79.8366040596311
"f1": 83.916407079888

Authors

About us

• Distilled roberta-base-squad2 (aka "tinyroberta-squad2")
• German BERT (aka "bert-base-german-cased")
• GermanQuAD and GermanDPR datasets and models (aka "gelectra-base-germanquad", "gbert-base-germandpr")

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