t5-base-TEDxJP-11body-0context

This model is a fine-tuned version of sonoisa/t5-base-japanese on the te_dx_jp dataset. It achieves the following results on the evaluation set:

• Loss: 0.8068
• Wer: 0.1976
• Mer: 0.1904
• Wil: 0.2816
• Wip: 0.7184
• Hits: 602335
• Substitutions: 75050
• Deletions: 39435
• Insertions: 27185
• Cer: 0.1625

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: 0.0001
• train_batch_size: 64
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Wer	Mer	Wil	Wip	Hits	Substitutions	Deletions	Insertions	Cer
0.8909	1.0	746	0.7722	0.3120	0.2861	0.3989	0.6011	558138	99887	58795	64983	0.2652
0.6786	2.0	1492	0.7021	0.2226	0.2122	0.3069	0.6931	592242	78773	45805	34978	0.1862
0.5627	3.0	2238	0.6996	0.2104	0.2016	0.2942	0.7058	597381	76593	42846	31392	0.1752
0.489	4.0	2984	0.7161	0.2030	0.1952	0.2865	0.7135	599808	75155	41857	28506	0.1684
0.4355	5.0	3730	0.7389	0.2000	0.1924	0.2837	0.7163	601815	75247	39758	28335	0.1651
0.3836	6.0	4476	0.7537	0.1992	0.1918	0.2829	0.7171	601846	75046	39928	27815	0.1640
0.3617	7.0	5222	0.7743	0.1995	0.1918	0.2832	0.7168	602287	75268	39265	28445	0.1642
0.3258	8.0	5968	0.7907	0.1971	0.1899	0.2809	0.7191	602800	74887	39133	27258	0.1620
0.3225	9.0	6714	0.8035	0.1981	0.1908	0.2823	0.7177	602418	75372	39030	27625	0.1630
0.3162	10.0	7460	0.8068	0.1976	0.1904	0.2816	0.7184	602335	75050	39435	27185	0.1625

Framework versions

• Transformers 4.12.5
• Pytorch 1.10.0+cu102
• Datasets 1.15.1
• Tokenizers 0.10.3