---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b64_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_b64_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: 0.3630

## 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: 8500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4525        | 0.4188 | 500  | 0.4043          |
| 0.4541        | 0.8375 | 1000 | 0.3992          |
| 0.4355        | 1.2563 | 1500 | 0.3946          |
| 0.4315        | 1.6750 | 2000 | 0.3966          |
| 0.4329        | 2.0938 | 2500 | 0.3881          |
| 0.4235        | 2.5126 | 3000 | 0.3829          |
| 0.4179        | 2.9313 | 3500 | 0.3775          |
| 0.4116        | 3.3501 | 4000 | 0.3739          |
| 0.4107        | 3.7688 | 4500 | 0.3721          |
| 0.4029        | 4.1876 | 5000 | 0.3693          |
| 0.409         | 4.6064 | 5500 | 0.3680          |
| 0.4061        | 5.0251 | 6000 | 0.3662          |
| 0.403         | 5.4439 | 6500 | 0.3654          |
| 0.3958        | 5.8626 | 7000 | 0.3630          |
| 0.3952        | 6.2814 | 7500 | 0.3635          |
| 0.3971        | 6.7002 | 8000 | 0.3627          |
| 0.4004        | 7.1189 | 8500 | 0.3630          |


### Framework versions

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