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# biobert-base-cased-v1.1-squad-finetuned-covdrobert

This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.1-squad](https://huggingface.co/dmis-lab/biobert-base-cased-v1.1-squad) on the covid_qa_deepset dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3959

## 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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 486  | 0.3787          |
| 0.161         | 2.0   | 972  | 0.3959          |


### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu102
- Datasets 1.16.1
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["covid_qa_deepset"], "model-index": [{"name": "biobert-base-cased-v1.1-squad-finetuned-covdrobert", "results": []}]}
transformers pytorch bert question-answering generated_from_trainer dataset:covid_qa_deepset endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-covid_qa_deepset #endpoints_compatible #region-us 

biobert-base-cased-v1.1-squad-finetuned-covdrobert
==================================================


This model is a fine-tuned version of dmis-lab/biobert-base-cased-v1.1-squad on the covid\_qa\_deepset dataset.
It achieves the following results on the evaluation set:


* Loss: 0.3959


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: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2


### Training results



### Framework versions


* Transformers 4.13.0
* Pytorch 1.10.0+cu102
* Datasets 1.16.1
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.10.0+cu102
* Datasets 1.16.1
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-covid_qa_deepset #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2 ### Training results ### Framework versions


* Transformers 4.13.0
* Pytorch 1.10.0+cu102
* Datasets 1.16.1
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-covid_qa_deepset #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 128
* eval\_batch\_size: 128
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 2### Training results### Framework versions


* Transformers 4.13.0
* Pytorch 1.10.0+cu102
* Datasets 1.16.1
* Tokenizers 0.10.3