kogpt2-base-v2-finetuned-klue-ner
This model is a fine-tuned version of klue/roberta-base on the klue dataset. It achieves the following results on the evaluation set:
- Loss: 0.3319
- F1: 0.3916
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 |
---|---|---|---|---|
0.4441 | 1.0 | 1313 | 0.3900 | 0.2831 |
0.287 | 2.0 | 2626 | 0.3430 | 0.3298 |
0.2229 | 3.0 | 3939 | 0.3313 | 0.3624 |
0.1769 | 4.0 | 5252 | 0.3319 | 0.3916 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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