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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: extractive-question-answering
results: []
duplicated_from: autoevaluate/extractive-question-answering
---
<!-- 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
|