Avitas8485's picture
update model card README.md
e7d58af
---
language:
- en
license: mit
base_model: Avitas8485/speecht5_tts_commonvoice_en_04
tags:
- text-to-speech
- generated_from_trainer
datasets:
- lj_speech
model-index:
- name: speecht5_tts_commonvoice_en_05
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_commonvoice_en_05
This model is a fine-tuned version of [Avitas8485/speecht5_tts_commonvoice_en_04](https://huggingface.co/Avitas8485/speecht5_tts_commonvoice_en_04) on the ljspeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3664
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.4078 | 1.36 | 1000 | 0.3700 |
| 0.3981 | 2.71 | 2000 | 0.3680 |
| 0.4026 | 4.07 | 3000 | 0.3666 |
| 0.4026 | 5.43 | 4000 | 0.3664 |
### Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3