bart-Finetuned-sum-full_note

NazzX1/bart-Finetuned-sum-full_note

bart-Finetuned-sum-full_note is a machine learning model from NazzX1. 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

38% of all-time downloads

All-time downloads

Public

Parameters

406M

1.6 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors1.6 GB · 100%

At a glance

Library: transformers
License: mit
Model type: bart
Access: Public
Created: Apr 14, 2025
Updated: Apr 14, 2025
SHA: 6349744c

Base models

facebook/bart-large-cnn

Model card

From the Hugging Face model README

bart-Finetuned-sum-full_note

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

Loss: 0.5946
Rouge1: 0.4524
Rouge2: 0.2947
Rougel: 0.3398

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
optimizer: Use OptimizerNames.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
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel
0.6824	1.0	1600	0.6274	0.4476	0.2884	0.3342
0.5366	2.0	3200	0.5946	0.4524	0.2947	0.3398

Framework versions

Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Library: transformers
Type: bart
License: mit
Created: Apr 14, 2025
Updated: Apr 14, 2025