ASR_KoBART_PostProcess – AI Model by yoona-J | AlphaNeural AI

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yoona-J/
ASR_KoBART_PostProcess

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text2text-generation

generated_from_trainer

digit82/kobart-summarization

endpoints_compatible

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ASR_KoBART_PostProcess

This model is a fine-tuned version of digit82/kobart-summarization on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.5180

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: 1e-05
train_batch_size: 16
eval_batch_size: 16
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
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	14	4.4617
5.3245	2.0	28	3.9843
4.0978	3.0	42	3.6403
4.0978	4.0	56	3.3431
3.5966	5.0	70	3.0924
3.2521	6.0	84	2.8834
3.2521	7.0	98	2.7240
2.944	8.0	112	2.6109
2.767	9.0	126	2.5419
2.6582	10.0	140	2.5180

Framework versions

Transformers 4.52.4
Pytorch 2.6.0+cu124
Datasets 2.14.4
Tokenizers 0.21.1