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End of training
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metadata
license: mit
base_model: facebook/mbart-large-50
tags:
  - translation
  - generated_from_trainer
metrics:
  - bleu
  - rouge
model-index:
  - name: mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.001
    results: []

mbart-large-50-en-es-translation-lr-1e-05-weight-decay-0.001

This model is a fine-tuned version of facebook/mbart-large-50 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9549
  • Bleu: 45.0307
  • Rouge: {'rouge1': 0.7049318825090395, 'rouge2': 0.5238048751750992, 'rougeL': 0.684187379601513, 'rougeLsum': 0.6843574853855577}

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: 1e-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: 4

Training results

Training Loss Epoch Step Validation Loss Bleu Rouge
1.4627 1.0 4500 1.0255 42.1880 {'rouge1': 0.6725633216905762, 'rouge2': 0.48605402524493657, 'rougeL': 0.6498853764470456, 'rougeLsum': 0.6501981166312041}
0.8878 2.0 9000 0.9572 44.1734 {'rouge1': 0.6912686406245903, 'rouge2': 0.5093695171345348, 'rougeL': 0.6701896043455414, 'rougeLsum': 0.6703473419504804}
0.7125 3.0 13500 0.9414 44.8709 {'rouge1': 0.7051197958532004, 'rouge2': 0.5210482863677958, 'rougeL': 0.6843075431636916, 'rougeLsum': 0.6846265298079588}
0.6092 4.0 18000 0.9549 45.0821 {'rouge1': 0.7047932899349161, 'rouge2': 0.523739339466653, 'rougeL': 0.6840127607742443, 'rougeLsum': 0.684202100852132}

Framework versions

  • Transformers 4.33.0.dev0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4.dev0
  • Tokenizers 0.13.3