BART-SUMMARIZATION-2

mzizo4110/BART-SUMMARIZATION-2

BART-SUMMARIZATION-2 is a machine learning model from mzizo4110. 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 peft. The card lists the license as mit.

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

Downloads · 30 days

16% of all-time downloads

All-time downloads

Public

Repo size

37.8 MB

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors18.9 MB · 93%

At a glance

Library: peft
License: mit
Access: Public
Created: May 15, 2025
Updated: May 16, 2025
SHA: d451012a

Base models

facebook/bart-large-cnn

Model card

From the Hugging Face model README

BART-SUMMARIZATION-2

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

Loss: 1.4067

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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: 1
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.5489	0.1470	250	1.4343
1.5375	0.2940	500	1.4284
1.5258	0.4410	750	1.4237
1.5197	0.5881	1000	1.4175
1.5166	0.7351	1250	1.4130
1.5125	0.8821	1500	1.4067

Framework versions

PEFT 0.14.0
Transformers 4.51.3
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1

Library: peft
License: mit
Created: May 15, 2025
Updated: May 16, 2025