t5-base-TEDxJP-1body-3context

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: 0.4926
• Wer: 0.1968
• Mer: 0.1894
• Wil: 0.2793
• Wip: 0.7207
• Hits: 55899
• Substitutions: 6836
• Deletions: 3636
• Insertions: 2590
• Cer: 0.1733

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
0.7082	1.0	746	0.5637	0.2626	0.2430	0.3355	0.6645	54301	7195	4875	5358	0.2552
0.6213	2.0	1492	0.5150	0.2068	0.1994	0.2899	0.7101	55107	6861	4403	2462	0.1866
0.5331	3.0	2238	0.4945	0.2038	0.1958	0.2858	0.7142	55551	6845	3975	2705	0.1816
0.5185	4.0	2984	0.4880	0.2003	0.1929	0.2831	0.7169	55639	6860	3872	2563	0.1779
0.4963	5.0	3730	0.4858	0.1988	0.1912	0.2810	0.7190	55837	6838	3696	2662	0.1772
0.4625	6.0	4476	0.4885	0.1964	0.1894	0.2799	0.7201	55785	6875	3711	2448	0.1720
0.4416	7.0	5222	0.4898	0.1962	0.1890	0.2788	0.7212	55870	6819	3682	2522	0.1726
0.4287	8.0	5968	0.4894	0.1968	0.1894	0.2790	0.7210	55889	6804	3678	2580	0.1743
0.4457	9.0	6714	0.4909	0.1964	0.1891	0.2792	0.7208	55919	6858	3594	2586	0.1739
0.4068	10.0	7460	0.4926	0.1968	0.1894	0.2793	0.7207	55899	6836	3636	2590	0.1733

Framework versions

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