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ko_gyeongsang_test – AI Model by yomilimi | AlphaNeural AI
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ko_gyeongsang_test
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
gogamza/kobart-base-v2
finetune
mit
endpoints_compatible
us
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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
