---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b64_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_b64_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: 0.3623

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 2000
- training_steps: 12000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.7129        | 0.4188  | 500   | 0.6066          |
| 0.5922        | 0.8375  | 1000  | 0.4980          |
| 0.5168        | 1.2563  | 1500  | 0.4579          |
| 0.4954        | 1.6750  | 2000  | 0.4383          |
| 0.4836        | 2.0938  | 2500  | 0.4208          |
| 0.4623        | 2.5126  | 3000  | 0.4098          |
| 0.4499        | 2.9313  | 3500  | 0.4003          |
| 0.4421        | 3.3501  | 4000  | 0.3942          |
| 0.4345        | 3.7688  | 4500  | 0.3894          |
| 0.4233        | 4.1876  | 5000  | 0.3840          |
| 0.4288        | 4.6064  | 5500  | 0.3808          |
| 0.4218        | 5.0251  | 6000  | 0.3775          |
| 0.4174        | 5.4439  | 6500  | 0.3746          |
| 0.4075        | 5.8626  | 7000  | 0.3744          |
| 0.4042        | 6.2814  | 7500  | 0.3715          |
| 0.4075        | 6.7002  | 8000  | 0.3695          |
| 0.4064        | 7.1189  | 8500  | 0.3666          |
| 0.4007        | 7.5377  | 9000  | 0.3663          |
| 0.399         | 7.9564  | 9500  | 0.3649          |
| 0.4152        | 8.3752  | 10000 | 0.3647          |
| 0.4033        | 8.7940  | 10500 | 0.3640          |
| 0.4011        | 9.2127  | 11000 | 0.3628          |
| 0.4002        | 9.6315  | 11500 | 0.3631          |
| 0.3975        | 10.0503 | 12000 | 0.3623          |


### Framework versions

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