---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: malay_dataset_checkpoint
  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. -->

# malay_dataset_checkpoint

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: 0.5938

## 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: 3
- eval_batch_size: 3
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8835        | 0.17  | 500  | 1.1947          |
| 1.156         | 0.34  | 1000 | 0.9847          |
| 1.0174        | 0.51  | 1500 | 0.8688          |
| 0.9117        | 0.68  | 2000 | 0.7840          |
| 0.8413        | 0.86  | 2500 | 0.7218          |
| 0.8081        | 1.03  | 3000 | 0.7093          |
| 0.7662        | 1.2   | 3500 | 0.6677          |
| 0.746         | 1.37  | 4000 | 0.6525          |
| 0.7318        | 1.54  | 4500 | 0.6492          |
| 0.7043        | 1.71  | 5000 | 0.6472          |
| 0.7157        | 1.88  | 5500 | 0.6153          |
| 0.6821        | 2.05  | 6000 | 0.6070          |
| 0.692         | 2.23  | 6500 | 0.6133          |
| 0.671         | 2.4   | 7000 | 0.6089          |
| 0.6676        | 2.57  | 7500 | 0.6000          |
| 0.6769        | 2.74  | 8000 | 0.5956          |
| 0.6612        | 2.91  | 8500 | 0.5938          |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2