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---
{}
---
---
language:
- en
license: mit
tags:
- question-answering
- SQuAD
- BERT
datasets:
- squad
metrics:
- f1
- em
model-index:
- name: squad-v2-bert-base-finetuned
results:
- task:
type: question-answering
name: SQuAD Question Answering
dataset:
type: squad_v2
name: SQuAD v2
split: validation
metrics:
- type: f1
value: 26.869992349988973
name: F1 Score
- type: em
value: 23.347090036216628
name: Exact Match
verified: true
---
# distilbert-finetuned-uncased
This model is fine-tuned on SQuAD v2 for question answering tasks.
## Training Procedure
- Number of Epochs: 4
- Learning Rate: 2e-05
- Batch Size: 128 (per device)
- Evaluation Strategy: Every 100 steps
- Save Strategy: Every 100 steps
- FP16 Training: Yes
## Evaluation Results
- Exact Match: 23.347090036216628
- F1 Score: 26.869992349988973
- Total: 11873
- Has Answer Exact: 38.630229419703106
- Has Answer F1: 45.686136837283904
- Has Answer Total: 5928
- No Answer Exact: 8.107653490328007
- No Answer F1: 8.107653490328007
- No Answer Total: 5945
- Best Exact: 50.11370336056599
- Best Exact Threshold: 0.0
- Best F1: 50.11370336056599
- Best F1 Threshold: 0.0
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