readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: m2m100_418M-finetuned-ko-to-en4
    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. -->
  
  # m2m100_418M-finetuned-ko-to-en4
  
  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: 0.4598
  - Bleu: 85.3745
  - Gen Len: 9.7522
  
  ## 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: 0.001
  - train_batch_size: 4
  - eval_batch_size: 4
  - seed: 42
  - gradient_accumulation_steps: 256
  - total_train_batch_size: 1024
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|
  | No log        | 1.0   | 105  | 1.8667          | 24.5072 | 9.523   |
  | No log        | 2.0   | 210  | 0.8581          | 57.9973 | 9.2779  |
  | No log        | 3.0   | 315  | 0.6587          | 69.4588 | 9.7399  |
  | No log        | 4.0   | 420  | 0.5762          | 74.5636 | 9.6775  |
  | 1.4539        | 5.0   | 525  | 0.5254          | 78.8897 | 9.6946  |
  | 1.4539        | 6.0   | 630  | 0.4952          | 81.0054 | 9.7073  |
  | 1.4539        | 7.0   | 735  | 0.4773          | 83.0792 | 9.7233  |
  | 1.4539        | 8.0   | 840  | 0.4669          | 84.4309 | 9.7429  |
  | 1.4539        | 9.0   | 945  | 0.4616          | 85.0965 | 9.749   |
  | 0.144         | 10.0  | 1050 | 0.4598          | 85.3745 | 9.7522  |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  