---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_kazakh_tts2_1
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_kazakh_tts2_1

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the KazakhTTS2 dataset (Mussakhojayeva, S., Khassanov, Y., & Varol, H.A. (2022). KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics. International Conference on Language Resources and Evaluation).
It achieves the following results on the evaluation set:
- Loss: 0.4600

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.725         | 0.06  | 100  | 0.6639          |
| 0.6132        | 0.11  | 200  | 0.5466          |
| 0.571         | 0.17  | 300  | 0.5207          |
| 0.5647        | 0.22  | 400  | 0.5120          |
| 0.5556        | 0.28  | 500  | 0.5047          |
| 0.5475        | 0.34  | 600  | 0.5003          |
| 0.5432        | 0.39  | 700  | 0.4975          |
| 0.5366        | 0.45  | 800  | 0.4944          |
| 0.5376        | 0.5   | 900  | 0.4913          |
| 0.5325        | 0.56  | 1000 | 0.4868          |
| 0.5281        | 0.62  | 1100 | 0.4861          |
| 0.5288        | 0.67  | 1200 | 0.4848          |
| 0.5251        | 0.73  | 1300 | 0.4825          |
| 0.5213        | 0.78  | 1400 | 0.4818          |
| 0.5225        | 0.84  | 1500 | 0.4823          |
| 0.5199        | 0.9   | 1600 | 0.4812          |
| 0.5211        | 0.95  | 1700 | 0.4816          |
| 0.5194        | 1.01  | 1800 | 0.4826          |
| 0.5224        | 1.06  | 1900 | 0.4798          |
| 0.5213        | 1.12  | 2000 | 0.4800          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2