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fodmrldg/
news_summarization_model

Name: news_summarization_model
Availability: InStock

transformers

safetensors

text2text-generation

generated_from_trainer

eenzeenee/t5-base-korean-summarization

finetune

text-generation-inference

endpoints_compatible

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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

fodmrldg/news_summarization_model

news_summarization_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fodmrldg/
news_summarization_model