---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b128_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_b128_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: 0.3140

## 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: 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 |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5174        | 0.8377  | 500  | 0.4794          |
| 0.4561        | 1.6754  | 1000 | 0.4022          |
| 0.4169        | 2.5131  | 1500 | 0.3854          |
| 0.4054        | 3.3508  | 2000 | 0.3649          |
| 0.3863        | 4.1885  | 2500 | 0.3528          |
| 0.3807        | 5.0262  | 3000 | 0.3480          |
| 0.3708        | 5.8639  | 3500 | 0.3432          |
| 0.366         | 6.7016  | 4000 | 0.3328          |
| 0.3575        | 7.5393  | 4500 | 0.3300          |
| 0.3607        | 8.3770  | 5000 | 0.3284          |
| 0.352         | 9.2147  | 5500 | 0.3232          |
| 0.3471        | 10.0524 | 6000 | 0.3189          |
| 0.3469        | 10.8901 | 6500 | 0.3171          |
| 0.3465        | 11.7277 | 7000 | 0.3161          |
| 0.3443        | 12.5654 | 7500 | 0.3159          |
| 0.3432        | 13.4031 | 8000 | 0.3140          |


### Framework versions

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