# Overview
German QA-Model finetuned on Question-Answer-Pairs for Bürgerbüro-Service-Documents

**Base model:** deepset/gelectra-large

**Finetuning** in sequential steps on:
  1. Machine-translated (en->de) SQuAD 1.0
  2. GermanQuAD: deepset/germanquad
  3. Custom LHM-QA-Dataset (>reference following<)

**Evaluation:** Reaches a performance of 70,0 F1-Score on LHM-QA-testdata
{"language": ["de"], "license": "mit", "datasets": ["squad", "deepset/germanquad"]}
transformers pytorch safetensors electra question-answering de dataset:squad dataset:deepset/germanquad license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #safetensors #electra #question-answering #de #dataset-squad #dataset-deepset/germanquad #license-mit #endpoints_compatible #region-us 

# Overview
German QA-Model finetuned on Question-Answer-Pairs for Bürgerbüro-Service-Documents

Base model: deepset/gelectra-large

Finetuning in sequential steps on:
  1. Machine-translated (en->de) SQuAD 1.0
  2. GermanQuAD: deepset/germanquad
  3. Custom LHM-QA-Dataset (>reference following<)

Evaluation: Reaches a performance of 70,0 F1-Score on LHM-QA-testdata
# Overview
German QA-Model finetuned on Question-Answer-Pairs for Bürgerbüro-Service-Documents

Base model: deepset/gelectra-large

Finetuning in sequential steps on:
  1. Machine-translated (en->de) SQuAD 1.0
  2. GermanQuAD: deepset/germanquad
  3. Custom LHM-QA-Dataset (>reference following<)

Evaluation: Reaches a performance of 70,0 F1-Score on LHM-QA-testdata
TAGS
#transformers #pytorch #safetensors #electra #question-answering #de #dataset-squad #dataset-deepset/germanquad #license-mit #endpoints_compatible #region-us 
 # Overview
German QA-Model finetuned on Question-Answer-Pairs for Bürgerbüro-Service-Documents

Base model: deepset/gelectra-large

Finetuning in sequential steps on:
  1. Machine-translated (en->de) SQuAD 1.0
  2. GermanQuAD: deepset/germanquad
  3. Custom LHM-QA-Dataset (>reference following<)

Evaluation: Reaches a performance of 70,0 F1-Score on LHM-QA-testdata