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: 0.4119
- F1: 0.3964
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: 3e-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: 5
Training results
Training Loss | Epoch | Step | Validation Loss | F1 |
---|---|---|---|---|
0.6174 | 1.0 | 876 | 0.5155 | 0.2295 |
0.4045 | 2.0 | 1752 | 0.4996 | 0.2834 |
0.3157 | 3.0 | 2628 | 0.4186 | 0.3107 |
0.2569 | 4.0 | 3504 | 0.4066 | 0.3805 |
0.2148 | 5.0 | 4380 | 0.4119 | 0.3964 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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