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mdeberta-v3-kor-further-ner
This model is a fine-tuned version of lighthouse/mdeberta-v3-base-kor-further on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0261
- Precision: 0.9436
- Recall: 0.9378
- F1: 0.9407
- Accuracy: 0.9947
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 357 | 0.0490 | 0.8634 | 0.8914 | 0.8772 | 0.9887 |
| 0.2165 | 2.0 | 714 | 0.0296 | 0.9276 | 0.9308 | 0.9292 | 0.9937 |
| 0.0314 | 3.0 | 1071 | 0.0281 | 0.9275 | 0.9299 | 0.9287 | 0.9937 |
| 0.0314 | 4.0 | 1428 | 0.0261 | 0.9436 | 0.9378 | 0.9407 | 0.9947 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
