LoRA_LED_all_aspects

floflodebilbao/LoRA_LED_all_aspects

LoRA_LED_all_aspects is a machine learning model from floflodebilbao. 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 apache-2.0.

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

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Hugging Face

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At a glance

Library: peft
License: apache-2.0
Access: Public
Created: Jul 31, 2025
Updated: Jul 31, 2025
SHA: 204c7625

Base models

allenai/led-base-16384

Model card

From the Hugging Face model README

LoRA_LED_all_aspects

This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 3.2585
Rouge1: 0.2961
Rouge2: 0.1042
Rougel: 0.234
Rougelsum: 0.2333
Gen Len: 29.3933
Bleu: 0.0577
Precisions: 0.1023
Brevity Penalty: 0.9031
Length Ratio: 0.9075
Translation Length: 3268.0
Reference Length: 3601.0
Precision: 0.8752
Recall: 0.8737
F1: 0.8744
Hashcode: roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)

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: 0.002
train_batch_size: 8
eval_batch_size: 8
seed: 42
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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len	Bleu	Precisions	Brevity Penalty	Length Ratio	Translation Length	Reference Length	Precision	Recall	F1	Hashcode
5.0003	1.0	38	3.3632	0.2751	0.1031	0.2271	0.2265	26.0267	0.0601	0.113	0.7896	0.8089	2913.0	3601.0	0.8795	0.8705	0.8749	roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
3.4616	2.0	76	3.2445	0.3023	0.104	0.237	0.2372	30.3467	0.065	0.1086	0.9019	0.9064	3264.0	3601.0	0.872	0.874	0.8729	roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
3.1933	3.0	114	3.2125	0.282	0.0998	0.2276	0.2264	29.2733	0.0576	0.1018	0.8859	0.892	3212.0	3601.0	0.8732	0.8729	0.873	roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
3.0156	4.0	152	3.2279	0.2848	0.1012	0.2294	0.2287	28.92	0.0611	0.1059	0.8862	0.8923	3213.0	3601.0	0.8769	0.8742	0.8755	roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)
2.874	5.0	190	3.2585	0.2961	0.1042	0.234	0.2333	29.3933	0.0577	0.1023	0.9031	0.9075	3268.0	3601.0	0.8752	0.8737	0.8744	roberta-large_L17_no-idf_version=0.3.12(hug_trans=4.53.1)

Framework versions

PEFT 0.15.2
Transformers 4.53.1
Pytorch 2.7.0+cu126
Datasets 3.6.0
Tokenizers 0.21.1

Library: peft
License: apache-2.0
Created: Jul 31, 2025
Updated: Jul 31, 2025