---
library_name: transformers
language:
- bn
license: mit
base_model: microsoft/speecht5_tts
tags:
- Bengali
- generated_from_trainer
datasets:
- ucalyptus/train-bn
model-index:
- name: SpeechT5-tuned-bn
  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-tuned-bn

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the train-bn dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5572

## 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
- training_steps: 1700
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.7601        | 0.1779 | 100  | 0.6865          |
| 0.7091        | 0.3559 | 200  | 0.6498          |
| 0.6819        | 0.5338 | 300  | 0.6345          |
| 0.6561        | 0.7117 | 400  | 0.6350          |
| 0.6353        | 0.8897 | 500  | 0.6044          |
| 0.6393        | 1.0676 | 600  | 0.5887          |
| 0.6402        | 1.2456 | 700  | 0.5906          |
| 0.6194        | 1.4235 | 800  | 0.5867          |
| 0.6127        | 1.6014 | 900  | 0.5788          |
| 0.608         | 1.7794 | 1000 | 0.5765          |
| 0.6129        | 1.9573 | 1100 | 0.5738          |
| 0.6044        | 2.1352 | 1200 | 0.5680          |
| 0.5894        | 2.3132 | 1300 | 0.5655          |
| 0.5952        | 2.4911 | 1400 | 0.5648          |
| 0.5963        | 2.6690 | 1500 | 0.5572          |
| 0.5889        | 2.8470 | 1600 | 0.5614          |
| 0.5897        | 3.0249 | 1700 | 0.5572          |


### Framework versions

- Transformers 4.47.0.dev0
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.20.1