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e2m_denoise_project

Text2Text Generation
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mbart
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e2m_denoise_project / README.md
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Added Noise to english source, fine-tuned with denoising, version mbart_endenoised_v1
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metadata
library_name: transformers
base_model: facebook/mbart-large-50-one-to-many-mmt
tags:
  - generated_from_trainer
model-index:
  - name: e2m_denoise_project
    results: []

e2m_denoise_project

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

  • Loss: 0.4057

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss
2.9598 1.0 125 0.4112
0.4495 2.0 250 0.4057

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3