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lala2211
This model is a fine-tuned version of monologg/kobert on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0105
- Accuracy: 0.7093
- F1: 0.7131
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
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.9365 | 1.0 | 1313 | 0.8612 | 0.6934 | 0.6953 |
| 0.5895 | 2.0 | 2626 | 0.9712 | 0.6871 | 0.6935 |
| 0.4931 | 3.0 | 3939 | 1.0105 | 0.7093 | 0.7131 |
Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
