T5-small-issues – AI Model by shebpamm | AlphaNeural AI

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shebpamm/
T5-small-issues

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text2text-generation

generated_from_trainer

google-t5/t5-small

text-generation-inference

endpoints_compatible

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T5-small-issues

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

Loss: 3.5636
Rouge1: 0.2138
Rouge2: 0.0795
Rougel: 0.193
Rougelsum: 0.1933
Gen Len: 14.5672

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	119	3.9060	0.1709	0.057	0.1512	0.1512	17.8298
No log	2.0	238	3.6568	0.2022	0.0738	0.1807	0.181	15.834
No log	3.0	357	3.5830	0.2112	0.08	0.1916	0.1918	14.916
No log	4.0	476	3.5636	0.2138	0.0795	0.193	0.1933	14.5672

Framework versions

Transformers 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1