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# biobert-v1.1-finetuned-pubmedqa-adapter

This model is a fine-tuned version of [dmis-lab/biobert-v1.1](https://huggingface.co/dmis-lab/biobert-v1.1) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0910
- Accuracy: 0.48

## 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: 0.003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 57   | 0.9848          | 0.58     |
| No log        | 2.0   | 114  | 0.8537          | 0.58     |
| No log        | 3.0   | 171  | 0.9565          | 0.42     |
| No log        | 4.0   | 228  | 0.9659          | 0.56     |
| No log        | 5.0   | 285  | 0.9763          | 0.6      |
| No log        | 6.0   | 342  | 1.0647          | 0.66     |
| No log        | 7.0   | 399  | 1.4305          | 0.6      |
| No log        | 8.0   | 456  | 2.0545          | 0.56     |
| 0.6957        | 9.0   | 513  | 2.2438          | 0.5      |
| 0.6957        | 10.0  | 570  | 2.0910          | 0.48     |


### Framework versions

- Transformers 4.8.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": [], "metrics": ["accuracy"], "model_index": [{"name": "biobert-v1.1-finetuned-pubmedqa-adapter", "results": [{"task": {"name": "Text Classification", "type": "text-classification"}, "metric": {"name": "Accuracy", "type": "accuracy", "value": 0.48}}]}]}
tensorboard generated_from_trainer region:us
TAGS
#tensorboard #generated_from_trainer #region-us 

biobert-v1.1-finetuned-pubmedqa-adapter
=======================================


This model is a fine-tuned version of dmis-lab/biobert-v1.1 on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0910
* Accuracy: 0.48


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: 0.003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10


### Training results



### Framework versions


* Transformers 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3
TAGS
#tensorboard #generated_from_trainer #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10 ### Training results ### Framework versions


* Transformers 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3
passage: TAGS
#tensorboard #generated_from_trainer #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.003
* train\_batch\_size: 8
* eval\_batch\_size: 8
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 10### Training results### Framework versions


* Transformers 4.8.2
* Pytorch 1.9.0+cu102
* Datasets 1.11.0
* Tokenizers 0.10.3