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autoevaluate
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extractive-question-answering-not-evaluated

Question Answering
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Inference Endpoints
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4
extractive-question-answering-not-evaluated
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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
duplicated_from: autoevaluate/extractive-question-answering
model-index:
- name: autoevaluate/extractive-question-answering-not-evaluated
  results:
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: autoevaluate/squad-sample
      type: autoevaluate/squad-sample
      config: autoevaluate--squad-sample
      split: test
    metrics:
    - type: f1
      value: 76.9929
      name: F1
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWY4NmY3MmUxMTI1YjYxOGQ4ZGJiNTExZWE2MGQ3NWY1MGNkMGZiNDA1M2FiNjM2ODBmMmM3NTM0MTIzYTE3OSIsInZlcnNpb24iOjF9.KCqAF5uiJ5MErIARbRt7ZQQZyMCxyQosMzoDk6Z-_-mLBJ3x8DTJYUKbSgd2QvA7tjnWhIq81ba4tJ0D5OvmBg
    - type: exact_match
      value: 70.0
      name: Exact Match
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTRmNTIxNDFhYzBmNDdkOGJmNmQ2YTBjODMxZWZkYzA5Njg2MDVlZjFmZTllMDQ4MzExM2MzMjcwMTc3NmY1MyIsInZlcnNpb24iOjF9.WwsKGMpmxBLVfpwA9qH7f_uVIpECcmkxxUUutHjLnraxZiPG-B_Z7InQ0dWtrtseEIkcEx-Y3u3rnEtzYhNbBA
    - type: loss
      value: 1.1083998680114746
      name: loss
      verified: true
      verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMzUwZGFjMjlhNzMzZGZjZTU5ZDZiYjg0YThiZTA1MDgzOWUxZTQxYmUzNGE2YWYwYTI2YTM1ZDJiNDdmMTcxZCIsInZlcnNpb24iOjF9.udy8AXJOg0hBuhBahq4XcbShp78SDBJz5phkvi4q8EuHEXuBQ1qIxrQbNDpoV2CG8_MBG9EPPtF5d32WiOn2BA
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# extractive-question-answering

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the squad dataset.
It achieves the following results on the evaluation set:

```
{'exact_match': 72.95175023651845,
 'f1': 81.85552166092225,
 'latency_in_seconds': 0.008616470915042614,
 'samples_per_second': 116.05679516125359,
 'total_time_in_seconds': 91.07609757200044}
```

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.263         | 1.0   | 5533 | 1.2169          |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1