---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
model-index:
- name: Hindi_SpeechT5_finetuned
  results: []
language:
- hi
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Hindi_SpeechT5_finetuned

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Validated split of Hindi data of [common_voice_17_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_17_0) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4524

## 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: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6856        | 0.3442 | 100  | 0.5976          |
| 0.5929        | 0.6885 | 200  | 0.5453          |
| 0.5554        | 1.0327 | 300  | 0.5130          |
| 0.5407        | 1.3769 | 400  | 0.5052          |
| 0.5318        | 1.7212 | 500  | 0.4847          |
| 0.5213        | 2.0654 | 600  | 0.4796          |
| 0.514         | 2.4096 | 700  | 0.4728          |
| 0.5065        | 2.7539 | 800  | 0.4703          |
| 0.5046        | 3.0981 | 900  | 0.4684          |
| 0.4976        | 3.4423 | 1000 | 0.4621          |
| 0.4929        | 3.7866 | 1100 | 0.4583          |
| 0.4791        | 4.1308 | 1200 | 0.4550          |
| 0.4823        | 4.4750 | 1300 | 0.4529          |
| 0.485         | 4.8193 | 1400 | 0.4506          |
| 0.4774        | 5.1635 | 1500 | 0.4524          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1