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# koelectra-base-v3-discriminator-finetuned-klue-v4

This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6219

## 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: 5e-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: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 5.4979        | 0.33  | 500  | 4.0470          |
| 3.2001        | 0.65  | 1000 | 2.3172          |
| 2.215         | 0.98  | 1500 | 1.9043          |
| 1.7849        | 1.31  | 2000 | 1.7181          |
| 1.6156        | 1.63  | 2500 | 1.5955          |
| 1.5295        | 1.96  | 3000 | 1.5071          |
| 1.2147        | 2.29  | 3500 | 1.5872          |
| 1.1727        | 2.61  | 4000 | 1.5104          |
| 1.1467        | 2.94  | 4500 | 1.6059          |
| 0.9972        | 3.27  | 5000 | 1.6523          |
| 0.9791        | 3.59  | 5500 | 1.6219          |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "koelectra-base-v3-discriminator-finetuned-klue-v4", "results": []}]}
transformers pytorch electra question-answering generated_from_trainer license:apache-2.0 endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 

koelectra-base-v3-discriminator-finetuned-klue-v4
=================================================


This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 1.6219


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: 5e-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: 20


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1
TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 20 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #license-apache-2.0 #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-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: 20### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.12.1