| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - squad_v2 |
| model-index: |
| - name: extractive_reader_nq_squad_v2 |
| results: [] |
| language: |
| - en |
| --- |
| |
| <!-- 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_reader_nq_squad_v2 |
|
|
| This model is a fine-tuned version of [ToluClassics/extractive_reader_nq](https://huggingface.co/ToluClassics/extractive_reader_nq) on the squad_v2 dataset. |
| |
| ## 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: 3e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5.0 |
| |
| ### Training results |
| |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.26.0 |
| - Pytorch 1.13.1+cu117 |
| - Datasets 2.8.0 |
| - Tokenizers 0.13.2 |
| |
| |
| ### Code Examples |
| |
| ```python |
| import torch |
| import numpy as np |
| from transformers import AutoTokenizer, AutoModelForQuestionAnswering |
| |
| tokenizer = AutoTokenizer.from_pretrained("ToluClassics/extractive_reader_nq_squad_v2") |
|
|
| model = AutoModelForQuestionAnswering.from_pretrained("ToluClassics/extractive_reader_nq_squad_v2") |
| |
| question = "" |
| context = "" |
| |
| inputs = tokenizer.encode(question, context, add_special_tokens=True, return_tensors="pt") |
|
|
| output = model(inputs) |
|
|
| answer_start = torch.argmax(output.start_logits) |
| answer_end = torch.argmax(output.end_logits) |
| if answer_end >= answer_start: |
| print(tokenizer.decode(inputs[0][answer_start:answer_end+1])) |
| ``` |
