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speecht5_tts

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metadata
language:
  - en
license: mit
base_model: microsoft/speecht5_tts
tags:
  - en_accent,mozilla,t5,common_voice_1_0
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_1_0
model-index:
  - name: SpeechT5 TTS English Accented
    results: []

SpeechT5 TTS English Accented

This model is a fine-tuned version of microsoft/speecht5_tts on the Common Voice dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5854

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • training_steps: 10000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.41 250 0.5448
0.6715 2.82 500 0.5147
0.6715 4.24 750 0.5225
0.5532 5.65 1000 0.5096
0.5532 7.06 1250 0.5293
0.5156 8.47 1500 0.5310
0.5156 9.89 1750 0.5417
0.4874 11.3 2000 0.5185
0.4874 12.71 2250 0.5112
0.4693 14.12 2500 0.5154
0.4693 15.54 2750 0.5148
0.4619 16.95 3000 0.5367
0.4619 18.36 3250 0.5207
0.447 19.77 3500 0.5318
0.447 21.19 3750 0.5286
0.4348 22.6 4000 0.5345
0.4348 24.01 4250 0.5362
0.4237 25.42 4500 0.5568
0.4237 26.84 4750 0.5352
0.4195 28.25 5000 0.5395
0.4195 29.66 5250 0.5487
0.4132 31.07 5500 0.5443
0.4132 32.49 5750 0.5491
0.3975 33.9 6000 0.5465
0.3975 35.31 6250 0.5505
0.396 36.72 6500 0.5450
0.396 38.14 6750 0.5510
0.3884 39.55 7000 0.5517
0.3884 40.96 7250 0.5685
0.383 42.37 7500 0.5622
0.383 43.79 7750 0.5659
0.3806 45.2 8000 0.5636
0.3806 46.61 8250 0.5681
0.3738 48.02 8500 0.5797
0.3738 49.44 8750 0.5741
0.3705 50.85 9000 0.5765
0.3705 52.26 9250 0.5770
0.364 53.67 9500 0.5854
0.364 55.08 9750 0.5806
0.36 56.5 10000 0.5854

Framework versions

  • Transformers 4.36.0.dev0
  • Pytorch 2.1.0+cu121
  • Datasets 2.15.0
  • Tokenizers 0.14.1