---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
model-index:
- name: test8k
  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. -->

# test8k

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5429

## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7829        | 0.76  | 100  | 0.6936          |
| 0.6812        | 1.53  | 200  | 0.6392          |
| 0.6544        | 2.29  | 300  | 0.6275          |
| 0.6337        | 3.05  | 400  | 0.6147          |
| 0.6214        | 3.81  | 500  | 0.5963          |
| 0.602         | 4.58  | 600  | 0.5894          |
| 0.6078        | 5.34  | 700  | 0.5902          |
| 0.5892        | 6.1   | 800  | 0.5854          |
| 0.5842        | 6.86  | 900  | 0.5751          |
| 0.5836        | 7.63  | 1000 | 0.5691          |
| 0.5712        | 8.39  | 1100 | 0.5722          |
| 0.5734        | 9.15  | 1200 | 0.5654          |
| 0.5669        | 9.91  | 1300 | 0.5539          |
| 0.5575        | 10.68 | 1400 | 0.5629          |
| 0.5638        | 11.44 | 1500 | 0.5594          |
| 0.5522        | 12.2  | 1600 | 0.5550          |
| 0.5585        | 12.96 | 1700 | 0.5515          |
| 0.5488        | 13.73 | 1800 | 0.5492          |
| 0.5536        | 14.49 | 1900 | 0.5579          |
| 0.5353        | 15.25 | 2000 | 0.5533          |
| 0.5379        | 16.02 | 2100 | 0.5434          |
| 0.5369        | 16.78 | 2200 | 0.5495          |
| 0.5375        | 17.54 | 2300 | 0.5441          |
| 0.5285        | 18.3  | 2400 | 0.5473          |
| 0.5262        | 19.07 | 2500 | 0.5369          |
| 0.5242        | 19.83 | 2600 | 0.5464          |
| 0.5219        | 20.59 | 2700 | 0.5414          |
| 0.5132        | 21.35 | 2800 | 0.5426          |
| 0.517         | 22.12 | 2900 | 0.5442          |
| 0.5097        | 22.88 | 3000 | 0.5429          |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.15.2