token_classification
This model is a fine-tuned version of klue/bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2401
- Precision: 0.5859
- Recall: 0.6590
- F1: 0.6203
- Accuracy: 0.9231
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: 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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 313 | 0.2617 | 0.5639 | 0.6304 | 0.5953 | 0.9161 |
| 0.3262 | 2.0 | 626 | 0.2401 | 0.5859 | 0.6590 | 0.6203 | 0.9231 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
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Model tree for Seogmin/token_classification
Base model
klue/bert-base