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# koelectra-base-v3-discriminator-finetuned-ner

This model is a fine-tuned version of [monologg/koelectra-base-v3-discriminator](https://huggingface.co/monologg/koelectra-base-v3-discriminator) on the klue dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1957
- Precision: 0.6665
- Recall: 0.7350
- F1: 0.6991
- Accuracy: 0.9396

## 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: 48
- eval_batch_size: 48
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 438  | 0.2588          | 0.5701    | 0.6655 | 0.6141 | 0.9212   |
| 0.4333        | 2.0   | 876  | 0.2060          | 0.6671    | 0.7134 | 0.6895 | 0.9373   |
| 0.1944        | 3.0   | 1314 | 0.1957          | 0.6665    | 0.7350 | 0.6991 | 0.9396   |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.12.0+cu102
- Datasets 1.14.0
- Tokenizers 0.10.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["klue"], "metrics": ["precision", "recall", "f1", "accuracy"], "model-index": [{"name": "koelectra-base-v3-discriminator-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "klue", "type": "klue", "args": "ner"}, "metrics": [{"type": "precision", "value": 0.6665182546749777, "name": "Precision"}, {"type": "recall", "value": 0.7350073648032546, "name": "Recall"}, {"type": "f1", "value": 0.6990893625537877, "name": "F1"}, {"type": "accuracy", "value": 0.9395764497172635, "name": "Accuracy"}]}]}]}
transformers pytorch electra token-classification generated_from_trainer dataset:klue license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #token-classification #generated_from_trainer #dataset-klue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

koelectra-base-v3-discriminator-finetuned-ner
=============================================


This model is a fine-tuned version of monologg/koelectra-base-v3-discriminator on the klue dataset.
It achieves the following results on the evaluation set:


* Loss: 0.1957
* Precision: 0.6665
* Recall: 0.7350
* F1: 0.6991
* Accuracy: 0.9396


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: 48
* eval\_batch\_size: 48
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3


### Training results



### Framework versions


* Transformers 4.11.3
* Pytorch 1.12.0+cu102
* Datasets 1.14.0
* Tokenizers 0.10.3



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.12.0+cu102
* Datasets 1.14.0
* Tokenizers 0.10.3
TAGS
#transformers #pytorch #electra #token-classification #generated_from_trainer #dataset-klue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3 ### Training results ### Framework versions


* Transformers 4.11.3
* Pytorch 1.12.0+cu102
* Datasets 1.14.0
* Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #electra #token-classification #generated_from_trainer #dataset-klue #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 48
* eval\_batch\_size: 48
* seed: 42
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 3### Training results### Framework versions


* Transformers 4.11.3
* Pytorch 1.12.0+cu102
* Datasets 1.14.0
* Tokenizers 0.10.3