metadata
license: mit
base_model: gogamza/kobart-base-v2
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: Gyeongsang_encoder
results: []
Gyeongsang_encoder
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: 0.0062
- Bleu: 91.4436
- Gen Len: 13.3478
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 |
|---|---|---|---|---|---|
| 0.0054 | 1.0 | 12910 | 0.0072 | 91.1948 | 13.3484 |
| 0.0052 | 2.0 | 25820 | 0.0063 | 91.3684 | 13.3464 |
| 0.0043 | 3.0 | 38730 | 0.0062 | 91.4436 | 13.3478 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1