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metadata
language:
  - ko
  - ja
base_model: facebook/mbart-large-50-many-to-many-mmt
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: mbartLarge_koja_37p
    results: []

mbartLarge_koja_37p

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: 0.8995
  • Bleu: 6.2934
  • Gen Len: 17.4862

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: linear
  • lr_scheduler_warmup_steps: 1500
  • num_epochs: 35

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
1.2712 0.48 5500 1.2204 3.0858 18.1085
1.0946 0.97 11000 1.0578 3.3162 17.8651
0.9546 1.45 16500 0.9688 5.6024 17.902
0.89 1.94 22000 0.9414 5.1453 17.6144
0.834 2.42 27500 0.9213 5.3985 17.6899
0.7439 2.91 33000 0.8995 6.2934 17.4862
0.6803 3.39 38500 0.9016 6.3565 17.8899
0.733 3.88 44000 0.9226 7.0351 17.6112
0.6601 4.36 49500 0.9807 5.3084 17.4292
0.6933 4.84 55000 0.9238 6.8389 17.5131

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu121
  • Datasets 2.14.6
  • Tokenizers 0.14.1