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ko-en_mbartLarge_exp5p_linear

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: 1.2308
  • Bleu: 26.2764
  • Gen Len: 18.3888

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: 500
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
1.7665 0.46 1000 1.6564 17.6773 18.7196
1.5688 0.93 2000 1.4939 20.8837 18.3983
1.457 1.39 3000 1.4350 21.9168 18.458
1.4107 1.86 4000 1.3752 22.8881 18.4826
1.3039 2.32 5000 1.3327 23.8115 18.4348
1.282 2.78 6000 1.3079 24.235 18.3561
1.2133 3.25 7000 1.2820 24.8877 18.5204
1.1787 3.71 8000 1.2580 25.2719 18.415
1.1154 4.18 9000 1.2543 25.5507 18.3528
1.0956 4.64 10000 1.2415 25.7284 18.5348
1.023 5.1 11000 1.2410 25.7912 18.3347
0.95 5.57 12000 1.2327 25.9921 18.2593
0.9476 6.03 13000 1.2631 25.829 18.3686
0.9061 6.5 14000 1.2548 25.8316 18.7481
0.9037 6.96 15000 1.2308 26.2764 18.3888
0.7431 7.42 16000 1.2716 25.9268 18.256
0.7526 7.89 17000 1.2655 25.9883 18.2052
0.6654 8.35 18000 1.3118 25.6866 18.2217
0.6953 8.82 19000 1.3050 25.8958 18.3387

Framework versions

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