---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: SpeechT5-Hausa-2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# SpeechT5-Hausa-2

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: 0.5086

## 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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5658        | 7.3733  | 200  | 0.5169          |
| 0.5266        | 14.7465 | 400  | 0.5300          |
| 0.4989        | 22.1198 | 600  | 0.4869          |
| 0.4747        | 29.4931 | 800  | 0.4763          |
| 0.4571        | 36.8664 | 1000 | 0.4736          |
| 0.4515        | 44.2396 | 1200 | 0.4751          |
| 0.4385        | 51.6129 | 1400 | 0.4884          |
| 0.4333        | 58.9862 | 1600 | 0.4969          |
| 0.429         | 66.3594 | 1800 | 0.5048          |
| 0.4198        | 73.7327 | 2000 | 0.5086          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1