---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: speecht5_finetuned_local_language_dataset_bn
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_local_language_dataset_bn

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: 0.6038

## 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: 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: 50
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8489        | 0.1675 | 100  | 0.7253          |
| 0.7415        | 0.3349 | 200  | 0.6669          |
| 0.6951        | 0.5024 | 300  | 0.6351          |
| 0.6798        | 0.6699 | 400  | 0.6267          |
| 0.6757        | 0.8373 | 500  | 0.6246          |
| 0.674         | 1.0048 | 600  | 0.6127          |
| 0.6728        | 1.1723 | 700  | 0.6087          |
| 0.6599        | 1.3398 | 800  | 0.6061          |
| 0.6527        | 1.5072 | 900  | 0.6048          |
| 0.6583        | 1.6747 | 1000 | 0.6038          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1