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---
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
|