|
--- |
|
license: mit |
|
base_model: microsoft/speecht5_tts |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: zlm_b128_le5_s8000 |
|
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. --> |
|
|
|
# zlm_b128_le5_s8000 |
|
|
|
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: 0.3662 |
|
|
|
## 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: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 8 |
|
- total_train_batch_size: 128 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 2000 |
|
- training_steps: 8000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-------:|:----:|:---------------:| |
|
| 0.6645 | 0.8377 | 500 | 0.5698 | |
|
| 0.5581 | 1.6754 | 1000 | 0.4794 | |
|
| 0.5045 | 2.5131 | 1500 | 0.4467 | |
|
| 0.4776 | 3.3508 | 2000 | 0.4236 | |
|
| 0.4553 | 4.1885 | 2500 | 0.4093 | |
|
| 0.4489 | 5.0262 | 3000 | 0.3968 | |
|
| 0.4337 | 5.8639 | 3500 | 0.3926 | |
|
| 0.4282 | 6.7016 | 4000 | 0.3837 | |
|
| 0.4188 | 7.5393 | 4500 | 0.3798 | |
|
| 0.4222 | 8.3770 | 5000 | 0.3784 | |
|
| 0.412 | 9.2147 | 5500 | 0.3729 | |
|
| 0.4056 | 10.0524 | 6000 | 0.3697 | |
|
| 0.4065 | 10.8901 | 6500 | 0.3685 | |
|
| 0.4069 | 11.7277 | 7000 | 0.3675 | |
|
| 0.4049 | 12.5654 | 7500 | 0.3666 | |
|
| 0.4044 | 13.4031 | 8000 | 0.3662 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
