speecht5_finetuned_google_fleurs_greek

This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3920

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: 2.5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 40

Training results

Training Loss Epoch Step Validation Loss
0.5174 1.0 583 0.4863
0.4948 2.0 1166 0.4611
0.4723 3.0 1749 0.4503
0.4763 4.0 2333 0.4438
0.4614 5.0 2916 0.4407
0.4569 6.0 3499 0.4387
0.4538 7.0 4082 0.4306
0.4539 8.0 4666 0.4282
0.4564 9.0 5249 0.4230
0.4493 10.0 5832 0.4222
0.445 11.0 6415 0.4190
0.4564 12.0 6999 0.4195
0.4381 13.0 7582 0.4161
0.4328 14.0 8165 0.4147
0.4424 15.0 8748 0.4140
0.4282 16.0 9332 0.4117
0.4349 17.0 9915 0.4090
0.4381 18.0 10498 0.4090
0.4328 19.0 11081 0.4073
0.4347 20.0 11665 0.4079
0.4293 21.0 12248 0.4055
0.4251 22.0 12831 0.4052
0.4359 23.0 13414 0.4023
0.4311 24.0 13998 0.4016
0.421 25.0 14581 0.4014
0.4162 26.0 15164 0.3991
0.4219 27.0 15747 0.3990
0.4247 28.0 16331 0.3989
0.4188 29.0 16914 0.3974
0.4229 30.0 17497 0.3976
0.4246 31.0 18080 0.3960
0.4219 32.0 18664 0.3956
0.4228 33.0 19247 0.3951
0.4183 34.0 19830 0.3946
0.4097 35.0 20413 0.3936
0.4245 36.0 20997 0.3935
0.4184 37.0 21580 0.3930
0.4198 38.0 22163 0.3937
0.4193 39.0 22746 0.3925
0.4096 39.98 23320 0.3920

Framework versions

  • Transformers 4.30.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.13.1
  • Tokenizers 0.13.3
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