| --- |
| 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: autoevaluate/squad-sample |
| type: autoevaluate/squad-sample |
| config: autoevaluate--squad-sample |
| split: test |
| metrics: |
| - name: Exact Match |
| type: exact_match |
| value: 70.0 |
| verified: true |
| - name: F1 |
| type: f1 |
| value: 76.9929 |
| 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 |
|
|
