---
license: mit
base_model: microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext
tags:
- generated_from_trainer
datasets:
- covid_qa_deepset
model-index:
- name: bert-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-covid

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the covid_qa_deepset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6900

## 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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.474         | 0.04  | 5    | 4.3730          |
| 3.9933        | 0.09  | 10   | 3.2783          |
| 3.0206        | 0.13  | 15   | 2.0289          |
| 1.9741        | 0.18  | 20   | 1.3879          |
| 1.4351        | 0.22  | 25   | 1.1733          |
| 1.5916        | 0.26  | 30   | 1.1623          |
| 0.5383        | 0.31  | 35   | 1.1952          |
| 0.7776        | 0.35  | 40   | 1.1920          |
| 1.1785        | 0.39  | 45   | 1.1216          |
| 1.1334        | 0.44  | 50   | 1.0412          |
| 0.7445        | 0.48  | 55   | 1.0829          |
| 0.6512        | 0.53  | 60   | 1.0443          |
| 0.7516        | 0.57  | 65   | 1.0089          |
| 0.5953        | 0.61  | 70   | 0.9273          |
| 0.8589        | 0.66  | 75   | 0.8947          |
| 0.7561        | 0.7   | 80   | 0.9009          |
| 0.9561        | 0.75  | 85   | 0.9006          |
| 0.7731        | 0.79  | 90   | 0.8482          |
| 0.8269        | 0.83  | 95   | 0.8380          |
| 0.9884        | 0.88  | 100  | 0.8200          |
| 0.9187        | 0.92  | 105  | 0.8775          |
| 0.585         | 0.96  | 110  | 0.8499          |
| 0.6835        | 1.01  | 115  | 0.8314          |
| 0.6668        | 1.05  | 120  | 0.7491          |
| 0.5558        | 1.1   | 125  | 0.7154          |
| 0.4491        | 1.14  | 130  | 0.8212          |
| 1.0667        | 1.18  | 135  | 0.8477          |
| 0.4472        | 1.23  | 140  | 0.7636          |
| 0.6892        | 1.27  | 145  | 0.7493          |
| 0.66          | 1.32  | 150  | 0.6932          |
| 0.5044        | 1.36  | 155  | 0.7675          |
| 0.5329        | 1.4   | 160  | 0.7406          |
| 0.2223        | 1.45  | 165  | 0.8099          |
| 0.5495        | 1.49  | 170  | 0.8758          |
| 0.5534        | 1.54  | 175  | 0.8476          |
| 0.4962        | 1.58  | 180  | 0.7953          |
| 0.7477        | 1.62  | 185  | 0.7610          |
| 0.7293        | 1.67  | 190  | 0.8357          |
| 0.6205        | 1.71  | 195  | 0.7339          |
| 0.5687        | 1.75  | 200  | 0.6908          |
| 0.884         | 1.8   | 205  | 0.6706          |
| 0.5928        | 1.84  | 210  | 0.6546          |
| 0.3209        | 1.89  | 215  | 0.6505          |
| 0.7585        | 1.93  | 220  | 0.6486          |
| 0.8501        | 1.97  | 225  | 0.6272          |
| 0.1664        | 2.02  | 230  | 0.6211          |
| 0.4483        | 2.06  | 235  | 0.6550          |
| 0.3361        | 2.11  | 240  | 0.6604          |
| 0.3085        | 2.15  | 245  | 0.6520          |
| 0.2407        | 2.19  | 250  | 0.6695          |
| 0.3418        | 2.24  | 255  | 0.6687          |
| 0.3165        | 2.28  | 260  | 0.6730          |
| 0.5811        | 2.32  | 265  | 0.6546          |
| 0.3516        | 2.37  | 270  | 0.6579          |
| 0.3136        | 2.41  | 275  | 0.6688          |
| 0.2508        | 2.46  | 280  | 0.6921          |
| 0.3463        | 2.5   | 285  | 0.7124          |
| 0.3603        | 2.54  | 290  | 0.7160          |
| 0.4455        | 2.59  | 295  | 0.6995          |
| 0.5433        | 2.63  | 300  | 0.6919          |
| 0.3411        | 2.68  | 305  | 0.6898          |
| 0.6065        | 2.72  | 310  | 0.6922          |
| 0.6258        | 2.76  | 315  | 0.6955          |
| 0.283         | 2.81  | 320  | 0.7008          |
| 0.6233        | 2.85  | 325  | 0.6988          |
| 0.3899        | 2.89  | 330  | 0.6949          |
| 0.238         | 2.94  | 335  | 0.6916          |
| 0.3166        | 2.98  | 340  | 0.6900          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1