t5-summarization – AI Model by JohnDoe70 | AlphaNeural AI

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JohnDoe70/
t5-summarization

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text2text-generation

generated_from_trainer

google-t5/t5-base

text-generation-inference

endpoints_compatible

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t5-base-question-answer-summarization

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

Loss: 0.1420
Rouge1: 87.2659
Rouge2: 79.1621
Rougel: 84.0716
Rougelsum: 84.0332

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: 5.6e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum
0.3593	1.0	450	0.1339	87.0068	78.4882	83.5134	83.4528
0.121	2.0	900	0.1273	87.3363	79.1644	83.7472	83.7456
0.0982	3.0	1350	0.1314	87.0066	78.3475	83.0262	82.9739
0.084	4.0	1800	0.1322	87.1678	78.7514	83.4642	83.441
0.074	5.0	2250	0.1345	87.2618	79.114	83.9859	83.9444
0.0685	6.0	2700	0.1378	87.1497	79.0628	83.958	83.9482
0.0609	7.0	3150	0.1419	86.993	78.781	83.8076	83.7681
0.0591	8.0	3600	0.1420	87.2659	79.1621	84.0716	84.0332

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2