|
--- |
|
license: mit |
|
base_model: microsoft/speecht5_tts |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: zlm_b32_le4_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_b32_le4_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: 0.3262 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 2 |
|
- 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: 2000 |
|
- training_steps: 8000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.5552 | 0.2094 | 500 | 0.4883 | |
|
| 0.4913 | 0.4188 | 1000 | 0.4266 | |
|
| 0.446 | 0.6283 | 1500 | 0.3975 | |
|
| 0.4222 | 0.8377 | 2000 | 0.3949 | |
|
| 0.4273 | 1.0471 | 2500 | 0.3829 | |
|
| 0.4028 | 1.2565 | 3000 | 0.3674 | |
|
| 0.3941 | 1.4660 | 3500 | 0.3616 | |
|
| 0.3871 | 1.6754 | 4000 | 0.3519 | |
|
| 0.3828 | 1.8848 | 4500 | 0.3493 | |
|
| 0.3954 | 2.0942 | 5000 | 0.3490 | |
|
| 0.381 | 2.3037 | 5500 | 0.3398 | |
|
| 0.372 | 2.5131 | 6000 | 0.3372 | |
|
| 0.3642 | 2.7225 | 6500 | 0.3314 | |
|
| 0.3692 | 2.9319 | 7000 | 0.3308 | |
|
| 0.3555 | 3.1414 | 7500 | 0.3283 | |
|
| 0.3536 | 3.3508 | 8000 | 0.3262 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
