t5-small-finetuned-qmsum – AI Model by ecat3rina | AlphaNeural AI

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ecat3rina/
t5-small-finetuned-qmsum

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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t5-small-finetuned-qmsum

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

Loss: 3.4617
Rouge1: 27.6423
Rouge2: 8.5163
Rougel: 23.1505

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
3.3956	1.0	126	3.5354	27.6519	8.0746	23.1321
3.407	2.0	252	3.5115	27.4959	8.1111	23.1004
3.36	3.0	378	3.4898	27.7611	8.3366	23.1863
3.3032	4.0	504	3.4804	27.5676	8.2376	23.1387
3.2602	5.0	630	3.4727	28.1638	8.6819	23.4878
3.258	6.0	756	3.4644	27.8802	8.5634	23.3815
3.2167	7.0	882	3.4626	27.649	8.5533	23.2101
3.203	8.0	1008	3.4617	27.6423	8.5163	23.1505

Framework versions

Transformers 4.42.4
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1