---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: bert-base-uncased-squad-v1-jpqd-ov-int8
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# bert-base-uncased-squad-v1-jpqd-ov-int8

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the squad dataset.
It was compressed using [NNCF](https://github.com/openvinotoolkit/nncf) with [Optimum
Intel](https://github.com/huggingface/optimum-intel#openvino) following the [JPQD question-answering
example](https://github.com/huggingface/optimum-intel/tree/main/examples/openvino/question-answering#joint-pruning-quantization-and-distillation-jpqd-for-bert-on-squad10).

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 16
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8.0
- mixed_precision_training: Native AMP

### Training results

```
***** eval metrics *****
  epoch            =     8.0
  eval_exact_match =  83.141
  eval_f1          = 89.5906
  eval_samples     =   10784
```

### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2