|
--- |
|
language: |
|
- zh |
|
license: mit |
|
base_model: GCYY/speecht5_finetuned_fleurs_zh |
|
tags: |
|
- text-to-speech |
|
- generated_from_trainer |
|
datasets: |
|
- google/fleurs |
|
model-index: |
|
- name: SpeechT5 TTS Chinese |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# SpeechT5 TTS Chinese |
|
|
|
This model is a fine-tuned version of [GCYY/speecht5_finetuned_fleurs_zh](https://huggingface.co/GCYY/speecht5_finetuned_fleurs_zh) on the fleurs dataset. |
|
It achieves the following results on the evaluation set: |
|
- eval_loss: 0.3956 |
|
- eval_runtime: 36.5499 |
|
- eval_samples_per_second: 12.586 |
|
- eval_steps_per_second: 1.587 |
|
- epoch: 15.44 |
|
- step: 2000 |
|
|
|
## 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: 5e-06 |
|
- 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: 500 |
|
- training_steps: 4000 |
|
|
|
### Framework versions |
|
|
|
- Transformers 4.33.3 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.14.5 |
|
- Tokenizers 0.13.3 |
|
|
