readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: ko-en-m2m
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
  should probably proofread and complete it, then remove this comment. -->
  
  # ko-en-m2m
  
  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.4282
  - Bleu: 25.8137
  - Gen Len: 10.9556
  
  ## 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: 0.0003
  - train_batch_size: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 6
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 0.5891        | 0.3   | 5000  | 0.7640          | 12.7212 | 10.465  |
  | 0.5653        | 0.6   | 10000 | 0.7211          | 13.4957 | 11.5844 |
  | 0.5464        | 0.91  | 15000 | 0.6875          | 13.5204 | 10.6604 |
  | 0.5254        | 1.21  | 20000 | 0.6690          | 14.5273 | 10.5754 |
  | 0.5308        | 1.51  | 25000 | 0.6757          | 14.1623 | 11.9493 |
  | 0.5192        | 1.81  | 30000 | 0.6458          | 15.1048 | 10.8811 |
  | 0.502         | 2.11  | 35000 | 0.6423          | 14.7989 | 11.047  |
  | 0.4971        | 2.42  | 40000 | 0.6259          | 15.6324 | 11.0428 |
  | 0.502         | 2.72  | 45000 | 0.6047          | 16.684  | 10.9814 |
  | 0.4544        | 3.02  | 50000 | 0.5834          | 16.9704 | 10.9722 |
  | 0.4541        | 3.32  | 55000 | 0.5722          | 17.6061 | 10.8485 |
  | 0.4362        | 3.63  | 60000 | 0.5523          | 19.1337 | 10.7972 |
  | 0.4285        | 3.93  | 65000 | 0.5325          | 19.4546 | 10.6665 |
  | 0.3851        | 4.23  | 70000 | 0.5159          | 20.4035 | 10.6171 |
  | 0.3891        | 4.53  | 75000 | 0.4926          | 21.8822 | 10.8857 |
  | 0.3602        | 4.83  | 80000 | 0.4740          | 22.737  | 11.0248 |
  | 0.336         | 5.14  | 85000 | 0.4570          | 23.7202 | 10.7115 |
  | 0.3355        | 5.44  | 90000 | 0.4415          | 24.9891 | 10.9077 |
  | 0.3244        | 5.74  | 95000 | 0.4282          | 25.8137 | 10.9556 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.0+cu116
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  