---
license: mit
base_model: timpal0l/mdeberta-v3-base-squad2
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: bert-covidqa-5
  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-covidqa-5

This model is a fine-tuned version of [timpal0l/mdeberta-v3-base-squad2](https://huggingface.co/timpal0l/mdeberta-v3-base-squad2) on the covid_qa_deepset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4190

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5956        | 0.04  | 5    | 0.4016          |
| 0.3741        | 0.09  | 10   | 0.3879          |
| 0.3405        | 0.13  | 15   | 0.4240          |
| 0.4372        | 0.18  | 20   | 0.4102          |
| 0.2592        | 0.22  | 25   | 0.4534          |
| 0.3534        | 0.26  | 30   | 0.4571          |
| 0.4268        | 0.31  | 35   | 0.4107          |
| 0.2663        | 0.35  | 40   | 0.4166          |
| 0.143         | 0.39  | 45   | 0.4345          |
| 0.2494        | 0.44  | 50   | 0.5575          |
| 0.8953        | 0.48  | 55   | 0.6172          |
| 0.5504        | 0.53  | 60   | 0.4879          |
| 0.6411        | 0.57  | 65   | 0.3718          |
| 0.5454        | 0.61  | 70   | 0.3929          |
| 0.4441        | 0.66  | 75   | 0.3641          |
| 0.2922        | 0.7   | 80   | 0.3638          |
| 0.491         | 0.75  | 85   | 0.3785          |
| 0.4362        | 0.79  | 90   | 0.3938          |
| 0.1633        | 0.83  | 95   | 0.4162          |
| 0.6762        | 0.88  | 100  | 0.4321          |
| 0.3111        | 0.92  | 105  | 0.4241          |
| 0.3453        | 0.96  | 110  | 0.4190          |


### Framework versions

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