readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: mbart-large-cc25-finetuned-hi-to-en-v2
    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. -->
  
  # mbart-large-cc25-finetuned-hi-to-en-v2
  
  This model is a fine-tuned version of [facebook/mbart-large-cc25](https://huggingface.co/facebook/mbart-large-cc25) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.8027
  - Bleu: 33.4814
  - Gen Len: 21.8974
  
  ## 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: 1
  - eval_batch_size: 1
  - seed: 42
  - gradient_accumulation_steps: 4
  - total_train_batch_size: 4
  - 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
  | 1.8971        | 1.0   | 3955  | 1.6015          | 19.3557 | 43.7594 |
  | 1.3266        | 2.0   | 7910  | 1.4917          | 19.1404 | 35.3155 |
  | 0.9906        | 3.0   | 11865 | 1.5354          | 26.999  | 26.7497 |
  | 0.6987        | 4.0   | 15820 | 1.6457          | 31.9572 | 23.4565 |
  | 0.5073        | 5.0   | 19775 | 1.8544          | 34.1169 | 22.1507 |
  | 0.3554        | 6.0   | 23730 | 2.0985          | 34.0746 | 22.2396 |
  | 0.2423        | 7.0   | 27685 | 2.2534          | 33.2205 | 22.2184 |
  | 0.1918        | 8.0   | 31640 | 2.4014          | 32.2001 | 22.635  |
  | 0.1423        | 9.0   | 35595 | 2.5067          | 32.4074 | 22.8716 |
  | 0.1105        | 10.0  | 39550 | 2.5618          | 33.1965 | 22.5905 |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.11.0+cu113
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  