---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_kazakh_tts2
  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. -->

# speecht5_finetuned_kazakh_tts2

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5067

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- 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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.7136        | 0.03  | 100  | 0.6539          |
| 0.6471        | 0.06  | 200  | 0.5934          |
| 0.5851        | 0.08  | 300  | 0.5392          |
| 0.5764        | 0.11  | 400  | 0.5275          |
| 0.5666        | 0.14  | 500  | 0.5213          |
| 0.5577        | 0.17  | 600  | 0.5138          |
| 0.5605        | 0.2   | 700  | 0.5115          |
| 0.5622        | 0.22  | 800  | 0.5088          |
| 0.5603        | 0.25  | 900  | 0.5082          |
| 0.558         | 0.28  | 1000 | 0.5067          |


### Framework versions

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