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metadata
base_model: facebook/mbart-large-50
library_name: peft
license: mit
tags:
  - generated_from_trainer
model-index:
  - name: mbart-large-50_Nepali_News_Summarization_0
    results: []
datasets:
  - caspro/Nepali_News_Dataset
language:
  - ne
metrics:
  - rouge
pipeline_tag: text2text-generation

mbart-large-50_Nepali_News_Summarization_0

This model is a fine-tuned version of facebook/mbart-large-50 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3697
  • Rouge-1 R: 0.3809
  • Rouge-1 P: 0.3915
  • Rouge-1 F: 0.3761
  • Rouge-2 R: 0.215
  • Rouge-2 P: 0.2209
  • Rouge-2 F: 0.2109
  • Rouge-l R: 0.3708
  • Rouge-l P: 0.3809
  • Rouge-l F: 0.3661
  • Gen Len: 13.9732

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: 0.0005
  • train_batch_size: 5
  • eval_batch_size: 5
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge-1 R Rouge-1 P Rouge-1 F Rouge-2 R Rouge-2 P Rouge-2 F Rouge-l R Rouge-l P Rouge-l F Gen Len
1.563 1.0 10191 1.4569 0.3599 0.3789 0.3581 0.1965 0.2082 0.1946 0.3499 0.3683 0.3481 13.8415
1.4053 2.0 20382 1.3963 0.3631 0.3927 0.367 0.203 0.2203 0.204 0.354 0.3827 0.3577 13.4601
1.2399 3.0 30573 1.3697 0.3809 0.3915 0.3761 0.215 0.2209 0.2109 0.3708 0.3809 0.3661 13.9732

Framework versions

  • PEFT 0.11.1
  • Transformers 4.42.3
  • Pytorch 2.1.2
  • Datasets 2.20.0
  • Tokenizers 0.19.1