readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: MarianMix_en-10
    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. -->
  
  # MarianMix_en-10
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-tatoeba-en-ja](https://huggingface.co/Helsinki-NLP/opus-tatoeba-en-ja) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0752
  - Bleu: 14.601
  - Gen Len: 45.8087
  
  ## 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: 0.0001
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 99
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 10
  - num_epochs: 5
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Gen Len  |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|
  | 2.1136        | 0.44  | 500  | 2.0044          | 0.2655  | 109.0201 |
  | 1.1422        | 0.89  | 1000 | 1.7516          | 1.4123  | 71.0     |
  | 0.9666        | 1.33  | 1500 | 1.5219          | 3.6611  | 64.6888  |
  | 0.8725        | 1.78  | 2000 | 1.3606          | 4.6539  | 77.1641  |
  | 0.7655        | 2.22  | 2500 | 1.2586          | 8.3456  | 60.3837  |
  | 0.7149        | 2.67  | 3000 | 1.1953          | 11.2247 | 50.5921  |
  | 0.6719        | 3.11  | 3500 | 1.1541          | 10.4303 | 54.3776  |
  | 0.6265        | 3.56  | 4000 | 1.1186          | 13.3231 | 48.283   |
  | 0.6157        | 4.0   | 4500 | 1.0929          | 13.8467 | 46.569   |
  | 0.5736        | 4.44  | 5000 | 1.0848          | 14.2731 | 45.5035  |
  | 0.5683        | 4.89  | 5500 | 1.0752          | 14.601  | 45.8087  |
  
  
  ### Framework versions
  
  - Transformers 4.12.5
  - Pytorch 1.9.1
  - Datasets 1.17.0
  - Tokenizers 0.10.3
  