ko_classification
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6939
- Accuracy: 0.6534
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: 32
- eval_batch_size: 32
- 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 | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 157 | 0.6581 | 0.6036 |
| No log | 2.0 | 314 | 0.6482 | 0.622 |
| No log | 3.0 | 471 | 0.6450 | 0.632 |
| 0.6484 | 4.0 | 628 | 0.6290 | 0.6488 |
| 0.6484 | 5.0 | 785 | 0.6388 | 0.6444 |
| 0.6484 | 6.0 | 942 | 0.6533 | 0.656 |
| 0.552 | 7.0 | 1099 | 0.6564 | 0.6522 |
| 0.552 | 8.0 | 1256 | 0.6864 | 0.6602 |
| 0.552 | 9.0 | 1413 | 0.6953 | 0.6496 |
| 0.4579 | 10.0 | 1570 | 0.6939 | 0.6534 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3