Summarization_Continue

mzizo4110/Summarization_Continue

Summarization_Continue 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 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: Apr 26, 2025
Updated: May 3, 2025
SHA: b52806ee

Base models

Model card

From the Hugging Face model README

Summarization_Continue

This model is a fine-tuned version of t5-small on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0784

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: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
1.103	0.2229	500	1.0905
1.0955	0.4458	1000	1.0865
1.0835	0.6687	1500	1.0834
1.0841	0.8916	2000	1.0814
1.0803	1.1141	2500	1.0802
1.0812	1.3370	3000	1.0788
1.0816	1.5599	3500	1.0781
1.0827	1.7828	4000	1.0784

Framework versions

PEFT 0.14.0
Transformers 4.51.1
Pytorch 2.5.1+cu124
Datasets 3.5.0
Tokenizers 0.21.0

Library: peft
License: apache-2.0
Created: Apr 26, 2025
Updated: May 3, 2025