---
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: 0.3566

## 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: 4
- 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 0.4378        | 0.8375  | 500  | 0.3956          |
| 0.4328        | 1.6750  | 1000 | 0.3922          |
| 0.4228        | 2.5126  | 1500 | 0.3871          |
| 0.4179        | 3.3501  | 2000 | 0.3843          |
| 0.409         | 4.1876  | 2500 | 0.3769          |
| 0.41          | 5.0251  | 3000 | 0.3739          |
| 0.4003        | 5.8626  | 3500 | 0.3709          |
| 0.4052        | 6.7002  | 4000 | 0.3680          |
| 0.397         | 7.5377  | 4500 | 0.3636          |
| 0.4007        | 8.3752  | 5000 | 0.3615          |
| 0.4022        | 9.2127  | 5500 | 0.3612          |
| 0.3896        | 10.0503 | 6000 | 0.3601          |
| 0.3911        | 10.8878 | 6500 | 0.3577          |
| 0.3949        | 11.7253 | 7000 | 0.3584          |
| 0.3948        | 12.5628 | 7500 | 0.3568          |
| 0.3877        | 13.4003 | 8000 | 0.3566          |


### Framework versions

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