readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - un_multi
  metrics:
  - bleu
  model-index:
  - name: m2m100_418M-evaluated-en-to-ar-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: un_multi
        type: un_multi
        args: ar-en
      metrics:
      - name: Bleu
        type: bleu
        value: 41.8577
  ---
  
  <!-- 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-2000instancesUNMULTI-leaningRate2e-05-batchSize8-regu1
  
  This model is a fine-tuned version of [facebook/m2m100_418M](https://huggingface.co/facebook/m2m100_418M) on the un_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3603
  - Bleu: 41.8577
  - Meteor: 0.4199
  - Gen Len: 41.9
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 11
  - mixed_precision_training: Native AMP
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    | Meteor | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|
  | 5.111         | 0.5   | 100  | 3.2467          | 29.5017 | 0.3371 | 42.425  |
  | 2.1491        | 1.0   | 200  | 1.0018          | 33.0563 | 0.3593 | 41.205  |
  | 0.5911        | 1.5   | 300  | 0.4159          | 34.5818 | 0.3705 | 42.0625 |
  | 0.3546        | 2.0   | 400  | 0.3723          | 36.6179 | 0.3823 | 40.925  |
  | 0.2487        | 2.5   | 500  | 0.3595          | 39.0331 | 0.3956 | 41.56   |
  | 0.2365        | 3.0   | 600  | 0.3485          | 39.5188 | 0.4023 | 41.6425 |
  | 0.1687        | 3.5   | 700  | 0.3542          | 40.1728 | 0.4043 | 42.61   |
  | 0.1791        | 4.0   | 800  | 0.3466          | 40.4858 | 0.4101 | 41.5575 |
  | 0.1196        | 4.5   | 900  | 0.3493          | 41.2457 | 0.4123 | 41.755  |
  | 0.1394        | 5.0   | 1000 | 0.3486          | 40.5606 | 0.4114 | 41.78   |
  | 0.0958        | 5.5   | 1100 | 0.3568          | 41.1873 | 0.4157 | 41.7275 |
  | 0.1043        | 6.0   | 1200 | 0.3557          | 41.2749 | 0.4165 | 41.935  |
  | 0.073         | 6.5   | 1300 | 0.3603          | 41.8577 | 0.4199 | 41.9    |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  