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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
model-index:
- name: SpeechT5-Hausa-9
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-Hausa-9
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: 0.6525
## 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: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.6188 | 1.6598 | 100 | 0.6391 |
| 0.5578 | 3.3195 | 200 | 0.6273 |
| 0.5346 | 4.9793 | 300 | 0.6454 |
| 0.5193 | 6.6390 | 400 | 0.6131 |
| 0.5011 | 8.2988 | 500 | 0.6113 |
| 0.5069 | 9.9585 | 600 | 0.6259 |
| 0.495 | 11.6183 | 700 | 0.6292 |
| 0.4835 | 13.2780 | 800 | 0.6238 |
| 0.4795 | 14.9378 | 900 | 0.6300 |
| 0.4747 | 16.5975 | 1000 | 0.6222 |
| 0.4746 | 18.2573 | 1100 | 0.6387 |
| 0.4683 | 19.9170 | 1200 | 0.6220 |
| 0.4591 | 21.5768 | 1300 | 0.6474 |
| 0.4593 | 23.2365 | 1400 | 0.6548 |
| 0.4567 | 24.8963 | 1500 | 0.6322 |
| 0.4529 | 26.5560 | 1600 | 0.6476 |
| 0.4495 | 28.2158 | 1700 | 0.6517 |
| 0.4477 | 29.8755 | 1800 | 0.6397 |
| 0.442 | 31.5353 | 1900 | 0.6557 |
| 0.4412 | 33.1950 | 2000 | 0.6525 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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