kogpt2-base-v2-finetuned-klue-ner
This model is a fine-tuned version of skt/kogpt2-base-v2 on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.4428
- F1: 0.4103
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: 24
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.6127 | 1.0 | 876 | 0.5474 | 0.1952 |
| 0.4134 | 2.0 | 1752 | 0.4974 | 0.2779 |
| 0.3241 | 3.0 | 2628 | 0.4630 | 0.3255 |
| 0.2612 | 4.0 | 3504 | 0.4374 | 0.3537 |
| 0.2143 | 5.0 | 4380 | 0.4187 | 0.3928 |
| 0.1744 | 6.0 | 5256 | 0.4428 | 0.4103 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3