t5_finetuned_paraphrase-1024 – AI Model by Ujjawal | AlphaNeural AI

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Ujjawal/
t5_finetuned_paraphrase-1024

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text2text-generation

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text-generation-inference

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t5_finetuned_paraphrase-1024

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

Loss: 0.7026
Rouge1: 69.0908
Rouge2: 51.3373
Rougel: 65.9952
Rougelsum: 65.9963
Gen Len: 17.9946

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: 8
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
0.9264	1.0	12500	0.8018	67.7403	48.7329	64.2684	64.273	18.0296
0.8654	2.0	25000	0.7572	68.256	49.8753	64.9795	64.9743	18.0071
0.8391	3.0	37500	0.7366	68.5695	50.4061	65.3434	65.3424	18.0047
0.8151	4.0	50000	0.7225	68.7762	50.6912	65.5711	65.561	17.9929
0.8068	5.0	62500	0.7134	68.8998	50.9785	65.7391	65.7475	17.9953
0.801	6.0	75000	0.7076	69.0179	51.1629	65.8718	65.8738	17.9952
0.7982	7.0	87500	0.7035	69.0643	51.2707	65.9447	65.9508	17.9959
0.784	8.0	100000	0.7026	69.0908	51.3373	65.9952	65.9963	17.9946

Framework versions

Transformers 4.27.3
Pytorch 1.7.1+cu101
Datasets 2.13.2
Tokenizers 0.13.2