---
license: mit
base_model: hung200504/bert-squadv2
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: bert-squad-covidqa
  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-squad-covidqa

This model is a fine-tuned version of [hung200504/bert-squadv2](https://huggingface.co/hung200504/bert-squadv2) on the covid_qa_deepset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5141

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.1636        | 0.09  | 5    | 1.4553          |
| 0.8433        | 0.18  | 10   | 0.6359          |
| 0.8245        | 0.26  | 15   | 0.5610          |
| 0.5916        | 0.35  | 20   | 0.5416          |
| 0.5899        | 0.44  | 25   | 0.5148          |
| 0.4838        | 0.53  | 30   | 0.4996          |
| 0.4501        | 0.61  | 35   | 0.4929          |
| 0.7377        | 0.7   | 40   | 0.4610          |
| 0.455         | 0.79  | 45   | 0.4645          |
| 0.478         | 0.88  | 50   | 0.4745          |
| 0.3672        | 0.96  | 55   | 0.4803          |
| 0.6509        | 1.05  | 60   | 0.4875          |
| 0.3094        | 1.14  | 65   | 0.5089          |
| 0.3203        | 1.23  | 70   | 0.5751          |
| 0.3955        | 1.32  | 75   | 0.5416          |
| 0.6197        | 1.4   | 80   | 0.4848          |
| 0.455         | 1.49  | 85   | 0.4716          |
| 0.4086        | 1.58  | 90   | 0.4738          |
| 0.5028        | 1.67  | 95   | 0.4818          |
| 0.4953        | 1.75  | 100  | 0.4867          |
| 0.557         | 1.84  | 105  | 0.4826          |
| 0.3139        | 1.93  | 110  | 0.4832          |
| 0.3217        | 2.02  | 115  | 0.4921          |
| 0.4175        | 2.11  | 120  | 0.5056          |
| 0.3471        | 2.19  | 125  | 0.5204          |
| 0.209         | 2.28  | 130  | 0.5321          |
| 0.5151        | 2.37  | 135  | 0.5285          |
| 0.441         | 2.46  | 140  | 0.5141          |
| 0.3022        | 2.54  | 145  | 0.5031          |
| 0.3789        | 2.63  | 150  | 0.5002          |
| 0.2917        | 2.72  | 155  | 0.5041          |
| 0.372         | 2.81  | 160  | 0.5097          |
| 0.4001        | 2.89  | 165  | 0.5105          |
| 0.1803        | 2.98  | 170  | 0.5141          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1