metadata
library_name: transformers
base_model: eenzeenee/t5-base-korean-summarization
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: news_summarization_model
results: []
news_summarization_model
This model is a fine-tuned version of eenzeenee/t5-base-korean-summarization on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2221
- Rouge1: 0.6031
- Rouge2: 0.4193
- Rougel: 0.5896
- Rougelsum: 0.5892
- Gen Len: 42.2714
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.523 | 0.4762 | 100 | 0.3847 | 0.4833 | 0.2872 | 0.4627 | 0.4654 | 41.7571 |
| 0.3377 | 0.9524 | 200 | 0.2590 | 0.5709 | 0.3929 | 0.5581 | 0.5564 | 41.7810 |
| 0.2641 | 1.4286 | 300 | 0.2334 | 0.5889 | 0.4018 | 0.5785 | 0.5781 | 42.5048 |
| 0.2361 | 1.9048 | 400 | 0.2221 | 0.6031 | 0.4193 | 0.5896 | 0.5892 | 42.2714 |
Framework versions
- Transformers 4.55.0
- Pytorch 2.6.0+cu124
- Datasets 4.0.0
- Tokenizers 0.21.4