|
|
--- |
|
|
license: mit |
|
|
base_model: microsoft/speecht5_tts |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: speecht5_finetuned_k_voice_v3 |
|
|
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_finetuned_k_voice_v3 |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4215 |
|
|
|
|
|
## 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: 2 |
|
|
- eval_batch_size: 8 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 4 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_steps: 200 |
|
|
- num_epochs: 1 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 0.6081 | 0.2579 | 500 | 0.5853 | |
|
|
| 0.5601 | 0.5159 | 1000 | 0.4924 | |
|
|
| 0.5331 | 0.7738 | 1500 | 0.4709 | |
|
|
| 0.5263 | 1.0317 | 2000 | 0.4698 | |
|
|
| 0.5151 | 1.2897 | 2500 | 0.4615 | |
|
|
| 0.5172 | 1.5476 | 3000 | 0.4618 | |
|
|
| 0.5109 | 1.8055 | 3500 | 0.4486 | |
|
|
| 0.5025 | 2.0635 | 4000 | 0.4461 | |
|
|
| 0.4822 | 2.3214 | 4500 | 0.4356 | |
|
|
| 0.4911 | 2.5793 | 5000 | 0.4439 | |
|
|
| 0.4931 | 2.8372 | 5500 | 0.4331 | |
|
|
| 0.4904 | 3.0952 | 6000 | 0.4304 | |
|
|
| 0.474 | 3.3531 | 6500 | 0.4330 | |
|
|
| 0.4716 | 3.6110 | 7000 | 0.4307 | |
|
|
| 0.4673 | 3.8690 | 7500 | 0.4274 | |
|
|
| 0.4654 | 4.1269 | 8000 | 0.4250 | |
|
|
| 0.4609 | 4.3848 | 8500 | 0.4215 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.40.1 |
|
|
- Pytorch 2.6.0 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.19.1 |
|
|
|
