metadata
language: en
license: apache-2.0
datasets:
- squad
metrics:
- squad
model-index:
- name: autoevaluate/distilbert-base-cased-distilled-squad
results:
- task:
type: question-answering
name: Question Answering
dataset:
name: autoevaluate/squad-sample
type: autoevaluate/squad-sample
config: autoevaluate--squad-sample
split: test
metrics:
- type: f1
value: 87.8248
name: F1
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTBiYzkyNGNmMWRhNDIwMDhhOTBlMzU2OTQyZTMxMzNiODM3YzA0Mjk3NzY0YTI0ZWNiZjRlMDIzM2EzY2E5OCIsInZlcnNpb24iOjF9.xEOZCY6PgAuoh1I9zox8ZNPv3uT-Nx1c9I1GCAYOtY0QJPMw47ph0f-dagKStf9tbLLtcE6XUz-72EZtK6mzAw
- type: exact_match
value: 84
name: Exact Match
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYTdlODFkNDgyNDU5YjU1NDE0ZjVjYWU0Mzk5ZTA2ODRjYWRhMTg1MjFiNTg5ODA0NjE5OGVkZDc3ZjQ5N2E0NyIsInZlcnNpb24iOjF9.OPqpfiA6kRUzYEwqiYz-WVUMSBSlNn0T9v4uJUUKeQ4k0L7SKAfkqbR0LAg9xm6rh0-KadiUznFn3zDH2XUpDQ
- type: loss
value: 0.9980762600898743
name: loss
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2Q0NDVkN2JlNmRmMmU1YzZhYWJiMDJhYmE0ZTUxOTA3MGEzMGMwYjI4M2EzNmYwY2FiNzMwOGIyYmUxYTIxZCIsInZlcnNpb24iOjF9.MQXuMC8iVbhMxSjgdMMOa9f1a_0ej7PoH2F_JbsOcYrfpt0c2q0KZmlasIaQFkjV-To62NhLts2oLWKgRQpwCw
DistilBERT base cased distilled SQuAD
Note: This model is a clone of
distilbert-base-cased-distilled-squad
for internal testing.
This model is a fine-tune checkpoint of DistilBERT-base-cased, fine-tuned using (a second step of) knowledge distillation on SQuAD v1.1. This model reaches a F1 score of 87.1 on the dev set (for comparison, BERT bert-base-cased version reaches a F1 score of 88.7).
Using the question answering Evaluator
from evaluate gives:
{'exact_match': 79.54588457899716,
'f1': 86.81181300991533,
'latency_in_seconds': 0.008683730778997168,
'samples_per_second': 115.15787689073015,
'total_time_in_seconds': 91.78703433400005}
which is roughly consistent with the official score.