Question Answering
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
Eval Results (legacy)
Instructions to use SiraH/bert-finetuned-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SiraH/bert-finetuned-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="SiraH/bert-finetuned-squad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("SiraH/bert-finetuned-squad") model = AutoModelForQuestionAnswering.from_pretrained("SiraH/bert-finetuned-squad") - Notebooks
- Google Colab
- Kaggle
Add evaluation results on the grocery config and train split of subjqa
#2
by autoevaluator HF Staff - opened
README.md
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type: f1
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value: 44.135
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verified: true
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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type: f1
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value: 44.135
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verified: true
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- task:
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type: question-answering
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name: Question Answering
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dataset:
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name: subjqa
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type: subjqa
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config: grocery
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split: train
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metrics:
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- name: Exact Match
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type: exact_match
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value: 5.625
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verified: true
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- name: F1
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type: f1
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value: 15.8411
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verified: true
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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