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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
