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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
base_model: bert-base-uncased
model-index:
- name: bert-base-uncased-squad-v1
results: []
---
<!-- 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. -->
# bert-base-uncased-squad-v1
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad dataset.
It was finetuned following the [Transformers Question Answering example](https://github.com/huggingface/transformers/tree/main/examples/pytorch/question-answering#fine-tuning-bert-on-squad10):
```
python run_qa.py \
--model_name_or_path bert-base-uncased \
--dataset_name squad \
--do_train \
--do_eval \
--per_device_train_batch_size 12 \
--learning_rate 3e-5 \
--num_train_epochs 2 \
--max_seq_length 384 \
--doc_stride 128 \
```
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2.0
### Training results
```
***** eval metrics *****
epoch = 2.0
eval_exact_match = 81.3434
eval_f1 = 88.7002
eval_samples = 10784
```
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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