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ko-en_mbartLarge_mid2

This model is a fine-tuned version of facebook/mbart-large-50-many-to-many-mmt on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3246
  • Bleu: 22.9623
  • Gen Len: 18.7197

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
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • total_eval_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
1.5377 0.23 2000 1.6122 17.2009 18.7106
1.3891 0.46 4000 1.5059 19.3345 18.7688
1.2812 0.7 6000 1.4348 20.6032 18.9022
1.2374 0.93 8000 1.4035 21.2391 18.8434
1.1734 1.16 10000 1.4039 21.304 18.9964
1.1531 1.39 12000 1.3694 21.9087 18.8573
1.1158 1.62 14000 1.3574 22.004 18.5485
1.0941 1.86 16000 1.3457 21.9785 18.7119
0.9809 2.09 18000 1.3495 22.7983 18.8011
0.9834 2.32 20000 1.3429 22.5654 18.9416
0.9981 2.55 22000 1.3246 22.9493 18.7364
1.0074 2.78 24000 1.3539 22.3874 18.4428
0.9752 3.02 26000 1.3587 22.1907 18.8139
0.8858 3.25 28000 1.3457 22.82 18.8021
0.8895 3.48 30000 1.3603 22.1575 18.5638

Framework versions

  • Transformers 4.34.0
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.5
  • Tokenizers 0.14.1
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