Edit model card

wav2vec2phone-large-xlsr-jp-jdrt5N-demo

This model is a fine-tuned version of jonatasgrosman/wav2vec2-large-xlsr-53-japanese on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3714
  • Wer: 0.4730
  • Cer: 0.5054

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: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 4
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Wer Cer
1.5238 1.0 567 1.3532 0.8709 0.6208
1.2812 2.0 1134 0.8674 0.6835 0.5633
1.1329 3.0 1701 0.7105 0.6164 0.5564
1.0267 4.0 2268 0.6111 0.5775 0.5401
1.0415 5.0 2835 0.5505 0.5499 0.5482
0.9767 6.0 3402 0.4986 0.5210 0.5204
1.0392 7.0 3969 0.4655 0.5082 0.5194
0.9235 8.0 4536 0.4457 0.4989 0.5136
0.9511 9.0 5103 0.4201 0.4917 0.5106
0.8998 10.0 5670 0.4031 0.4869 0.5081
0.8883 11.0 6237 0.3920 0.4814 0.5107
0.856 12.0 6804 0.3834 0.4790 0.5094
0.8814 13.0 7371 0.3772 0.4761 0.5081
0.8352 14.0 7938 0.3737 0.4735 0.5052
0.9001 15.0 8505 0.3714 0.4730 0.5054

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.13.1
  • Tokenizers 0.13.3
Downloads last month
3
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for mskhattori/wav2vec2phone-large-xlsr-jp-jdrt5N-demo

Finetuned
(6)
this model