---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: Speect5-common-voice-Hindi
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Speect5-common-voice-Hindi

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4800

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6618        | 0.3445 | 100  | 0.6072          |
| 0.5936        | 0.6891 | 200  | 0.5618          |
| 0.5591        | 1.0336 | 300  | 0.5116          |
| 0.5412        | 1.3781 | 400  | 0.5120          |
| 0.5361        | 1.7227 | 500  | 0.4981          |
| 0.5272        | 2.0672 | 600  | 0.4922          |
| 0.5175        | 2.4117 | 700  | 0.4816          |
| 0.5179        | 2.7562 | 800  | 0.4800          |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1