mbart-sinhala-summarization

MVeeW/mbart-sinhala-summarization

mbart-sinhala-summarization is a machine learning model from MVeeW. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

4% of all-time downloads

All-time downloads

153

Public

Parameters

611M

29.4 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors2.4 GB · 99%

At a glance

Library: transformers
License: mit
Model type: mbart
Access: Public
Created: Oct 27, 2025
Updated: Oct 28, 2025
SHA: cceec5c3

Base models

facebook/mbart-large-50

Model card

From the Hugging Face model README

mbart-sinhala-summarization

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: 0.7119

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: 2
eval_batch_size: 2
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.8444	1.0	1625	0.6918
0.6061	2.0	3250	0.6834
0.4733	3.0	4875	0.7119

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1

Library: transformers
Type: mbart
License: mit
Created: Oct 27, 2025
Updated: Oct 28, 2025