SWivid/F5-TTS

400k steps into training, still heavy halucinating/unintelligible

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#1.283 geöffnet am 28. März 2026

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Beschreibung

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  • This template is only for usage issues encountered.
  • I have thoroughly reviewed the project documentation but couldn't find information to solve my problem.
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Environment Details

runpod/pytorch:2.4.0-py3.11-cuda12.4.1-devel-ubuntu22.04

Steps to Reproduce

This is the training config that I use with my dataset of 130 hours of clean Serbian speech:

  exp_name:               F5TTS_v1_Base
  tokenizer:              char
  mixed_precision:        bf16
  learning_rate:          7.5e-05
  batch_size_per_gpu:     20189
  batch_size_type:        frame
  max_samples:            64
  grad_accumulation_steps: 1
  max_grad_norm:          1
  epochs:                 434
  num_warmup_updates:     3779
  save_per_updates:       5000
  keep_last_n_checkpoints: 1
  last_per_updates:       10000
  logger:                 tensorboard
  dataset:                serbian
  finetune:               false (training from scratch)
  dataset_size:           60,948 samples / 132.05 hours
  gpu:                    NVIDIA A40 (46GB)

after 3 days of training and ~400k steps, inferenced audio is still halucinating and repeating some parts of the word or the whole words, sometimes also unintelligible.

Loss curve loss curve

Learninig rate learning rate

✔️ Expected Behavior

referenced audio: https://voca.ro/1iSJaiUm5CHz referenced text: u tom komitetu dobijamo vrlo vrlo opširne biografije kandidata, sa kojima vodimo razgovor i biramo ih, čak i ispitujemo.

❌ Actual Behavior

inferenced text: (same as referenced text) inferenced audio: https://voca.ro/1mT0JkcugloJ (this is with EMA enabled, without EMA is much worse)

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