readme: ---
  license: apache-2.0
  language:
  - tok
  - en
  tags:
  - generated_from_trainer
  - translation
  metrics:
  - bleu
  model-index:
  - name: toki-en-mt
    results: []
  widget:
  - text: "toki! mi jan Ton. mi lon ma Tawan."
  - text: "soweli li toki ala toki e toki Inli?"
  ---
  
  <!-- 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. -->
  
  # toki-en-mt
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ROMANCE-en](https://huggingface.co/Helsinki-NLP/opus-mt-ROMANCE-en) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2840
  - Bleu: 26.7612
  - Gen Len: 9.0631
  
  ## 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: 2e-05
  - 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: 10
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu    | Gen Len |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 1.7228        | 1.0   | 1260  | 1.4572          | 19.9464 | 9.2177  |
  | 1.3182        | 2.0   | 2520  | 1.3356          | 22.4628 | 9.1263  |
  | 1.1241        | 3.0   | 3780  | 1.3028          | 23.5152 | 9.0462  |
  | 0.9995        | 4.0   | 5040  | 1.2784          | 23.9526 | 9.1697  |
  | 0.8945        | 5.0   | 6300  | 1.2739          | 24.7707 | 9.0914  |
  | 0.8331        | 6.0   | 7560  | 1.2725          | 25.3477 | 9.0518  |
  | 0.7641        | 7.0   | 8820  | 1.2770          | 26.165  | 9.0245  |
  | 0.7163        | 8.0   | 10080 | 1.2809          | 25.8053 | 9.0933  |
  | 0.6886        | 9.0   | 11340 | 1.2799          | 26.5752 | 9.0669  |
  | 0.6627        | 10.0  | 12600 | 1.2840          | 26.7612 | 9.0631  |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  