---
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
---

<!-- 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-50_Nepali_News_Summarization_0

This model is a fine-tuned version of [facebook/mbart-large-50](https://huggingface.co/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