
# DistilBERT base cased distilled SQuAD

> Note: This model is a clone of [`distilbert-base-cased-distilled-squad`](https://huggingface.co/distilbert-base-cased-distilled-squad) for internal testing.

This model is a fine-tune checkpoint of [DistilBERT-base-cased](https://huggingface.co/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.
{"language": "en", "license": "apache-2.0", "datasets": ["squad"], "metrics": ["squad"]}
transformers pytorch tf rust distilbert question-answering en dataset:squad license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #tf #rust #distilbert #question-answering #en #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 


# 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:



which is roughly consistent with the official score.
# 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:



which is roughly consistent with the official score.
TAGS
#transformers #pytorch #tf #rust #distilbert #question-answering #en #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 
 # 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:



which is roughly consistent with the official score.
passage: TAGS
#transformers #pytorch #tf #rust #distilbert #question-answering #en #dataset-squad #license-apache-2.0 #endpoints_compatible #region-us 
# 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:



which is roughly consistent with the official score.