t5-large-multiwoz – AI Model by jinlmsft | AlphaNeural AI

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jinlmsft/
t5-large-multiwoz

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text2text-generation

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text-generation-inference

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t5-large-multiwoz

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

Loss: 0.0064
Acc: 1.0
True Num: 56671
Num: 56776

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: 5e-05
train_batch_size: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Acc	True Num	Num
0.1261	1.13	1000	0.0933	0.98	55574	56776
0.0951	2.25	2000	0.0655	0.98	55867	56776
0.0774	3.38	3000	0.0480	0.99	56047	56776
0.0584	4.51	4000	0.0334	0.99	56252	56776
0.042	5.64	5000	0.0222	0.99	56411	56776
0.0329	6.76	6000	0.0139	1.0	56502	56776
0.0254	7.89	7000	0.0094	1.0	56626	56776
0.0214	9.02	8000	0.0070	1.0	56659	56776

Framework versions

Transformers 4.12.5
Pytorch 1.10.0+cu102
Datasets 1.15.1
Tokenizers 0.10.3