---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b32_le5_s12000
  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_le5_s12000

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: 0.3707

## 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: 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: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.7211        | 0.2094 | 500   | 0.6148          |
| 0.6059        | 0.4188 | 1000  | 0.5140          |
| 0.5347        | 0.6283 | 1500  | 0.4725          |
| 0.4888        | 0.8377 | 2000  | 0.4612          |
| 0.4923        | 1.0471 | 2500  | 0.4283          |
| 0.466         | 1.2565 | 3000  | 0.4163          |
| 0.4535        | 1.4660 | 3500  | 0.4090          |
| 0.4442        | 1.6754 | 4000  | 0.4009          |
| 0.4423        | 1.8848 | 4500  | 0.3955          |
| 0.4539        | 2.0942 | 5000  | 0.3916          |
| 0.4416        | 2.3037 | 5500  | 0.3870          |
| 0.4306        | 2.5131 | 6000  | 0.3856          |
| 0.4242        | 2.7225 | 6500  | 0.3819          |
| 0.426         | 2.9319 | 7000  | 0.3814          |
| 0.4105        | 3.1414 | 7500  | 0.3787          |
| 0.4077        | 3.3508 | 8000  | 0.3750          |
| 0.4106        | 3.5602 | 8500  | 0.3748          |
| 0.4228        | 3.7696 | 9000  | 0.3728          |
| 0.4101        | 3.9791 | 9500  | 0.3719          |
| 0.4209        | 4.1885 | 10000 | 0.3707          |
| 0.4091        | 4.3979 | 10500 | 0.3712          |
| 0.4061        | 4.6073 | 11000 | 0.3715          |
| 0.4169        | 4.8168 | 11500 | 0.3700          |
| 0.4088        | 5.0262 | 12000 | 0.3707          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1