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klue-roberta-large-klue-crime-2-ner
This model is a fine-tuned version of soddokayo/klue-roberta-large-klue-ner on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5080
- Precision: 0.0727
- Recall: 0.0449
- F1: 0.0556
- Accuracy: 0.8794
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-06
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 1.0363 | 0.0 | 0.0 | 0.0 | 0.8425 |
| No log | 2.0 | 14 | 0.8076 | 0.0 | 0.0 | 0.0 | 0.8501 |
| No log | 3.0 | 21 | 0.6843 | 0.0 | 0.0 | 0.0 | 0.8554 |
| No log | 4.0 | 28 | 0.6184 | 0.0 | 0.0 | 0.0 | 0.8595 |
| No log | 5.0 | 35 | 0.5803 | 0.0 | 0.0 | 0.0 | 0.8618 |
| No log | 6.0 | 42 | 0.5546 | 0.0 | 0.0 | 0.0 | 0.8706 |
| No log | 7.0 | 49 | 0.5338 | 0.0189 | 0.0112 | 0.0141 | 0.8741 |
| No log | 8.0 | 56 | 0.5195 | 0.0370 | 0.0225 | 0.0280 | 0.8753 |
| No log | 9.0 | 63 | 0.5111 | 0.0545 | 0.0337 | 0.0417 | 0.8770 |
| No log | 10.0 | 70 | 0.5080 | 0.0727 | 0.0449 | 0.0556 | 0.8794 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cpu
- Datasets 2.12.0
- Tokenizers 0.11.0
