readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - opus100
  metrics:
  - bleu
  model-index:
  - name: m2m100_418M-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: opus100
        type: opus100
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 13.1835
  ---
  
  <!-- 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-evaluated-en-to-ar-2000instancesopus-leaningRate2e-05-batchSize16-20epoch-1
  
  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the opus100 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3640
  - Bleu: 13.1835
  - Meteor: 0.1189
  - Gen Len: 17.72
  
  ## 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: 20
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 6.1776        | 1.0   | 100  | 3.8904          | 10.5866 | 0.0995 | 16.64   |
  | 2.4531        | 2.0   | 200  | 1.0928          | 12.3452 | 0.1108 | 17.0575 |
  | 0.512         | 3.0   | 300  | 0.3625          | 10.5224 | 0.0982 | 17.2575 |
  | 0.1924        | 4.0   | 400  | 0.3342          | 12.4242 | 0.1098 | 16.6325 |
  | 0.1227        | 5.0   | 500  | 0.3403          | 13.0526 | 0.1185 | 17.3475 |
  | 0.0889        | 6.0   | 600  | 0.3481          | 13.1323 | 0.1133 | 17.815  |
  | 0.0651        | 7.0   | 700  | 0.3601          | 12.6684 | 0.1133 | 17.3525 |
  | 0.0533        | 8.0   | 800  | 0.3640          | 13.1835 | 0.1189 | 17.72   |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  