t5-small-devices-sum-ver2 – AI Model by Wizounovziki | AlphaNeural AI

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t5-small-devices-sum-ver2

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t5-small-devices-sum-ver2

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

Loss: 0.3679
Rouge1: 90.6465
Rouge2: 65.2833
Rougel: 90.6707
Rougelsum: 90.7313
Gen Len: 4.4702

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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	91	1.0957	58.9566	33.4113	58.8004	58.8863	4.8308
No log	2.0	182	0.7017	78.9566	49.9716	78.9338	78.9643	4.3329
No log	3.0	273	0.5386	84.8786	56.9622	84.8204	84.9117	4.4577
No log	4.0	364	0.4693	87.9792	61.0779	87.8795	88.0098	4.4383
No log	5.0	455	0.4273	89.4667	63.1994	89.4169	89.5197	4.4743
1.0586	6.0	546	0.4002	89.6456	63.5041	89.6062	89.7042	4.4452
1.0586	7.0	637	0.3848	89.9993	64.2505	89.9775	90.0651	4.423
1.0586	8.0	728	0.3752	90.4249	64.819	90.4434	90.5111	4.4799
1.0586	9.0	819	0.3703	90.4689	65.0086	90.4954	90.5632	4.4632
1.0586	10.0	910	0.3679	90.6465	65.2833	90.6707	90.7313	4.4702

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6