---
license: apache-2.0
base_model: google-bert/bert-base-uncased
tags:
- question-answering
- nlp
- generated_from_trainer
model-index:
- name: bert-qa-mash-covid
  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-qa-mash-covid

This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co./google-bert/bert-base-uncased) on the mashqa_covid_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2132

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 329  | 1.3919          |
| 1.6774        | 2.0   | 658  | 1.2387          |
| 1.6774        | 3.0   | 987  | 1.2132          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2