Hugging Face's logo

JBZhang2342
/
speecht5_tts

Text-to-Audio
Transformers
TensorBoard
Safetensors
English
speecht5
en_accent,mozilla,t5,common_voice_1_0
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
speecht5_tts / README.md
JBZhang2342's picture
JBZhang2342
End of training
d1e2091
preview code
|
raw
history blame
3.58 kB
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: 0.5154

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: 2
  • eval_batch_size: 2
  • 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 2.72 250 0.6947
0.7897 5.43 500 0.5278
0.7897 8.15 750 0.5005
0.5429 10.87 1000 0.4842
0.5429 13.59 1250 0.4830
0.4997 16.3 1500 0.4912
0.4997 19.02 1750 0.4820
0.4712 21.74 2000 0.4835
0.4712 24.46 2250 0.4840
0.4621 27.17 2500 0.4925
0.4621 29.89 2750 0.4855
0.4507 32.61 3000 0.4882
0.4507 35.33 3250 0.5065
0.4445 38.04 3500 0.5033
0.4445 40.76 3750 0.4991
0.4345 43.48 4000 0.4950
0.4345 46.2 4250 0.4986
0.4306 48.91 4500 0.5026
0.4306 51.63 4750 0.4986
0.4272 54.35 5000 0.5048
0.4272 57.07 5250 0.4967
0.4234 59.78 5500 0.5011
0.4234 62.5 5750 0.5017
0.4187 65.22 6000 0.5047
0.4187 67.93 6250 0.5041
0.4188 70.65 6500 0.5064
0.4188 73.37 6750 0.5164
0.4108 76.09 7000 0.5133
0.4108 78.8 7250 0.5086
0.4118 81.52 7500 0.5070
0.4118 84.24 7750 0.5093
0.4082 86.96 8000 0.5155
0.4082 89.67 8250 0.5089
0.407 92.39 8500 0.5134
0.407 95.11 8750 0.5056
0.407 97.83 9000 0.5154
0.407 100.54 9250 0.5108
0.4062 103.26 9500 0.5112
0.4062 105.98 9750 0.5122
0.4052 108.7 10000 0.5154

Framework versions

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