metadata
license: mit
base_model: gogamza/kobart-base-v2
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: ko_gyeongsang_test
results: []
ko_gyeongsang_test
This model is a fine-tuned version of gogamza/kobart-base-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.7493
- Bleu: 90.5462
- Gen Len: 20.0
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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 3.7799 | 1.0 | 12910 | 3.7647 | 89.6987 | 20.0 |
| 3.7679 | 2.0 | 25820 | 3.7528 | 90.4226 | 20.0 |
| 3.757 | 3.0 | 38730 | 3.7493 | 90.5462 | 20.0 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1