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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
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