metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - klue
metrics:
  - f1
base_model: monologg/koelectra-base-v3-discriminator
model-index:
  - name: kobert-finetuned-klue-ner
    results:
      - task:
          type: token-classification
          name: Token Classification
        dataset:
          name: klue
          type: klue
          config: ner
          split: validation
          args: ner
        metrics:
          - type: f1
            value: 0.26395413647583404
            name: F1

kobert-finetuned-klue-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: 0.4238
F1: 0.2640

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: 4

Training results

Training Loss	Epoch	Step	Validation Loss	F1
0.5975	1.0	1313	0.5314	0.1794
0.4068	2.0	2626	0.4611	0.2331
0.3366	3.0	3939	0.4264	0.2598
0.2933	4.0	5252	0.4238	0.2640

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3