mrm8488 / spanbert-finetuned-squadv1

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Total runs: 55
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7-day runs: 23
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Model's Last Updated: April 04 2023
question-answering

Introduction of spanbert-finetuned-squadv1

Model Details of spanbert-finetuned-squadv1

SpanBERT (spanbert-base-cased) fine-tuned on SQuAD v1.1

SpanBERT created by Facebook Research and fine-tuned on SQuAD 1.1 for Q&A downstream task.

Details of SpanBERT

A pre-training method that is designed to better represent and predict spans of text.

SpanBERT: Improving Pre-training by Representing and Predicting Spans

Details of the downstream task (Q&A) - Dataset

SQuAD 1.1 contains 100,000+ question-answer pairs on 500+ articles.

Dataset Split # samples
SQuAD1.1 train 87.7k
SQuAD1.1 eval 10.6k
Model training

The model was trained on a Tesla P100 GPU and 25GB of RAM. The script for fine tuning can be found here

Results:
Metric # Value
EM 85.49
F1 91.98
Raw metrics:
{
  "exact": 85.49668874172185,
  "f1": 91.9845699540379,
  "total": 10570,
  "HasAns_exact": 85.49668874172185,
  "HasAns_f1": 91.9845699540379,
  "HasAns_total": 10570,
  "best_exact": 85.49668874172185,
  "best_exact_thresh": 0.0,
  "best_f1": 91.9845699540379,
  "best_f1_thresh": 0.0
}
Comparison:
Model EM F1 score
SpanBert official repo - 92.4*
spanbert-finetuned-squadv1 85.49 91.98
Model in action

Fast usage with pipelines :

from transformers import pipeline

qa_pipeline = pipeline(
    "question-answering",
    model="mrm8488/spanbert-finetuned-squadv1",
    tokenizer="mrm8488/spanbert-finetuned-squadv1"
)

qa_pipeline({
    'context': "Manuel Romero has been working hardly in the repository hugginface/transformers lately",
    'question': "Who has been working hard for hugginface/transformers lately?"

})

Created by Manuel Romero/@mrm8488 | LinkedIn

Made with in Spain

Runs of mrm8488 spanbert-finetuned-squadv1 on huggingface.co

55
Total runs
0
24-hour runs
23
3-day runs
23
7-day runs
47
30-day runs

More Information About spanbert-finetuned-squadv1 huggingface.co Model

spanbert-finetuned-squadv1 huggingface.co

spanbert-finetuned-squadv1 huggingface.co is an AI model on huggingface.co that provides spanbert-finetuned-squadv1's model effect (), which can be used instantly with this mrm8488 spanbert-finetuned-squadv1 model. huggingface.co supports a free trial of the spanbert-finetuned-squadv1 model, and also provides paid use of the spanbert-finetuned-squadv1. Support call spanbert-finetuned-squadv1 model through api, including Node.js, Python, http.

spanbert-finetuned-squadv1 huggingface.co Url

https://huggingface.co/mrm8488/spanbert-finetuned-squadv1

mrm8488 spanbert-finetuned-squadv1 online free

spanbert-finetuned-squadv1 huggingface.co is an online trial and call api platform, which integrates spanbert-finetuned-squadv1's modeling effects, including api services, and provides a free online trial of spanbert-finetuned-squadv1, you can try spanbert-finetuned-squadv1 online for free by clicking the link below.

mrm8488 spanbert-finetuned-squadv1 online free url in huggingface.co:

https://huggingface.co/mrm8488/spanbert-finetuned-squadv1

spanbert-finetuned-squadv1 install

spanbert-finetuned-squadv1 is an open source model from GitHub that offers a free installation service, and any user can find spanbert-finetuned-squadv1 on GitHub to install. At the same time, huggingface.co provides the effect of spanbert-finetuned-squadv1 install, users can directly use spanbert-finetuned-squadv1 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

spanbert-finetuned-squadv1 install url in huggingface.co:

https://huggingface.co/mrm8488/spanbert-finetuned-squadv1

Url of spanbert-finetuned-squadv1

spanbert-finetuned-squadv1 huggingface.co Url

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