t5-base-TEDxJP-1body-10context

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: 0.3833
• Wer: 0.1983
• Mer: 0.1900
• Wil: 0.2778
• Wip: 0.7222
• Hits: 56229
• Substitutions: 6686
• Deletions: 3593
• Insertions: 2909
• Cer: 0.1823

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
0.5641	1.0	746	0.4426	0.2336	0.2212	0.3143	0.6857	54711	7183	4614	3742	0.2238
0.4867	2.0	1492	0.4017	0.2045	0.1972	0.2863	0.7137	55378	6764	4366	2470	0.1853
0.4257	3.0	2238	0.3831	0.2008	0.1933	0.2826	0.7174	55715	6788	4005	2560	0.1784
0.4038	4.0	2984	0.3797	0.1963	0.1890	0.2776	0.7224	56028	6731	3749	2578	0.1748
0.3817	5.0	3730	0.3769	0.1944	0.1877	0.2758	0.7242	55926	6663	3919	2345	0.1730
0.3467	6.0	4476	0.3806	0.2111	0.2002	0.2876	0.7124	56082	6688	3738	3616	0.1916
0.3361	7.0	5222	0.3797	0.1977	0.1897	0.2780	0.7220	56173	6721	3614	2816	0.1785
0.3107	8.0	5968	0.3814	0.1993	0.1910	0.2792	0.7208	56167	6720	3621	2916	0.1839
0.3141	9.0	6714	0.3820	0.1991	0.1907	0.2787	0.7213	56201	6709	3598	2933	0.1859
0.3122	10.0	7460	0.3833	0.1983	0.1900	0.2778	0.7222	56229	6686	3593	2909	0.1823

Framework versions

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