---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: extractive-question-answering
  results:
  - task:
      type: question-answering
      name: Question Answering
    dataset:
      name: squad
      type: squad
      config: plain_text
      split: validation
    metrics:
    - name: Loss
      type: loss
      value: 1.2488619089126587
      verified: true
    - name: exact_match
      type: exact_match
      value: 72.5436
      verified: true
    - name: f1
      type: f1
      value: 81.8688
      verified: true
---

<!-- 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