--- license: cc-by-nc-sa-4.0 tags: - generated_from_trainer datasets: - klue metrics: - f1 model-index: - name: kogpt2-base-v2-finetuned-klue-ner results: - task: name: Token Classification type: token-classification dataset: name: klue type: klue config: ner split: validation args: ner metrics: - name: F1 type: f1 value: 0.7404764644953389 --- # kogpt2-base-v2-finetuned-klue-ner This model is a fine-tuned version of [skt/kogpt2-base-v2](https://huggingface.co/skt/kogpt2-base-v2) on the klue dataset. It achieves the following results on the evaluation set: - Loss: 0.3849 - F1: 0.7405 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 0.2667 | 1.0 | 1313 | 0.2522 | 0.7073 | | 0.173 | 2.0 | 2626 | 0.2498 | 0.7313 | | 0.1237 | 3.0 | 3939 | 0.2660 | 0.7330 | | 0.0861 | 4.0 | 5252 | 0.3104 | 0.7423 | | 0.0592 | 5.0 | 6565 | 0.3849 | 0.7405 | ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu118 - Datasets 2.12.0 - Tokenizers 0.13.3