readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - hindi_english_machine_translation
  metrics:
  - bleu
  model-index:
  - name: mbart-large-cc25-ind_finetun-en-to-hi
    results:
    - task:
        name: Sequence-to-sequence Language Modeling
        type: text2text-generation
      dataset:
        name: hindi_english_machine_translation
        type: hindi_english_machine_translation
        args: hi-en
      metrics:
      - name: Bleu
        type: bleu
        value: 7.8242
  ---
  
  <!-- 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. -->
  
  # mbart-large-cc25-ind_finetun-en-to-hi
  
  This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on the hindi_english_machine_translation dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8148
  - Bleu: 7.8242
  - Gen Len: 75.28
  
  ## 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: 1
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu   | Gen Len |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
  | 3.3247        | 1.0   | 620  | 1.8148          | 7.8242 | 75.28   |
  
  
  ### Framework versions
  
  - Transformers 4.19.1
  - Pytorch 1.11.0+cu102
  - Datasets 1.18.0
  - Tokenizers 0.12.1
  