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metadata
library_name: transformers
language:
  - en
license: mit
base_model: microsoft/speecht5_tts
tags:
  - English
  - generated_from_trainer
datasets:
  - Yassmen/TTS_English_Technical_data
model-index:
  - name: SpeechT5-fine-tune-en
    results: []

SpeechT5-fine-tune-en

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

  • Loss: 0.4479

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: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 32
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 3.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
5.7875 0.1791 50 0.6062
4.5876 0.3583 100 0.5088
4.4072 0.5374 150 0.4908
4.3177 0.7165 200 0.4883
4.1852 0.8957 250 0.4808
4.1009 1.0748 300 0.4691
4.0833 1.2539 350 0.4677
4.0461 1.4330 400 0.4643
4.0024 1.6122 450 0.4587
3.9729 1.7913 500 0.4593
3.9057 1.9704 550 0.4555
3.8765 2.1496 600 0.4567
3.9148 2.3287 650 0.4541
3.8446 2.5078 700 0.4503
3.8321 2.6870 750 0.4511
3.8683 2.8661 800 0.4479

Framework versions

  • Transformers 4.46.0.dev0
  • Pytorch 2.4.1+cu121
  • Datasets 3.0.2
  • Tokenizers 0.20.1