|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: microsoft/speecht5_tts |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: speecht5_improved_data_w_ljspeech |
|
|
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_improved_data_w_ljspeech |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5702 |
|
|
|
|
|
## 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: 2 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 8 |
|
|
- total_train_batch_size: 64 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- training_steps: 3000 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 0.9234 | 0.8097 | 250 | 0.7694 | |
|
|
| 0.7666 | 1.6194 | 500 | 0.6657 | |
|
|
| 0.6923 | 2.4291 | 750 | 0.6291 | |
|
|
| 0.6783 | 3.2389 | 1000 | 0.6109 | |
|
|
| 0.6572 | 4.0486 | 1250 | 0.5961 | |
|
|
| 0.6631 | 4.8583 | 1500 | 0.5909 | |
|
|
| 0.6413 | 5.6680 | 1750 | 0.5809 | |
|
|
| 0.6471 | 6.4777 | 2000 | 0.5798 | |
|
|
| 0.6336 | 7.2874 | 2250 | 0.5733 | |
|
|
| 0.6353 | 8.0972 | 2500 | 0.5723 | |
|
|
| 0.6257 | 8.9069 | 2750 | 0.5700 | |
|
|
| 0.632 | 9.7166 | 3000 | 0.5702 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.44.2 |
|
|
- Pytorch 2.1.2 |
|
|
- Datasets 2.17.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
