metadata
library_name: transformers
base_model: monologg/koelectra-small-v3-discriminator
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: koelectra
results: []
koelectra
This model is a fine-tuned version of monologg/koelectra-small-v3-discriminator on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5279
- Accuracy: 0.7425
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 100 | 0.6898 | 0.5925 |
| No log | 2.0 | 200 | 0.6713 | 0.6425 |
| No log | 3.0 | 300 | 0.6305 | 0.69 |
| No log | 4.0 | 400 | 0.5867 | 0.715 |
| 0.6422 | 5.0 | 500 | 0.5630 | 0.7075 |
| 0.6422 | 6.0 | 600 | 0.5326 | 0.745 |
| 0.6422 | 7.0 | 700 | 0.5395 | 0.745 |
| 0.6422 | 8.0 | 800 | 0.5281 | 0.7425 |
| 0.6422 | 9.0 | 900 | 0.5445 | 0.7275 |
| 0.4493 | 10.0 | 1000 | 0.5279 | 0.7425 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2