t5-base-TEDxJP-1body-1context

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: 0.5061
• Wer: 0.1990
• Mer: 0.1913
• Wil: 0.2823
• Wip: 0.7177
• Hits: 55830
• Substitutions: 6943
• Deletions: 3598
• Insertions: 2664
• Cer: 0.1763

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
0.7277	1.0	746	0.5799	0.2384	0.2256	0.3188	0.6812	54323	7170	4878	3777	0.2371
0.6278	2.0	1492	0.5254	0.2070	0.1997	0.2905	0.7095	55045	6885	4441	2412	0.1962
0.5411	3.0	2238	0.5076	0.2022	0.1950	0.2858	0.7142	55413	6902	4056	2463	0.1805
0.53	4.0	2984	0.5020	0.1979	0.1911	0.2814	0.7186	55599	6849	3923	2362	0.1761
0.5094	5.0	3730	0.4999	0.1987	0.1915	0.2828	0.7172	55651	6944	3776	2465	0.1742
0.4783	6.0	4476	0.5016	0.1985	0.1914	0.2826	0.7174	55684	6947	3740	2490	0.1753
0.4479	7.0	5222	0.5035	0.1976	0.1905	0.2819	0.7181	55726	6961	3684	2468	0.1733
0.4539	8.0	5968	0.5022	0.1967	0.1896	0.2807	0.7193	55795	6938	3638	2477	0.1729
0.4632	9.0	6714	0.5034	0.1991	0.1913	0.2824	0.7176	55844	6942	3585	2687	0.1758
0.4201	10.0	7460	0.5061	0.1990	0.1913	0.2823	0.7177	55830	6943	3598	2664	0.1763

Framework versions

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