---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_tts-wolof
  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_tts-wolof

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3697

## 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: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 255000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5033        | 0.9989  | 562   | 0.4592          |
| 0.471         | 1.9996  | 1125  | 0.4319          |
| 0.4603        | 2.9984  | 1687  | 0.4224          |
| 0.4496        | 3.9991  | 2250  | 0.4135          |
| 0.4418        | 4.9998  | 2813  | 0.4090          |
| 0.4296        | 5.9987  | 3375  | 0.4001          |
| 0.425         | 6.9993  | 3938  | 0.3950          |
| 0.4197        | 8.0     | 4501  | 0.3927          |
| 0.4173        | 8.9989  | 5063  | 0.3888          |
| 0.4133        | 9.9996  | 5626  | 0.3852          |
| 0.4112        | 10.9984 | 6188  | 0.3832          |
| 0.4072        | 11.9991 | 6751  | 0.3808          |
| 0.404         | 12.9998 | 7314  | 0.3788          |
| 0.4055        | 13.9987 | 7876  | 0.3792          |
| 0.401         | 14.9993 | 8439  | 0.3759          |
| 0.3988        | 16.0    | 9002  | 0.3755          |
| 0.3984        | 16.9989 | 9564  | 0.3761          |
| 0.3992        | 17.9996 | 10127 | 0.3735          |
| 0.392         | 18.9984 | 10689 | 0.3731          |
| 0.393         | 19.9991 | 11252 | 0.3730          |
| 0.3945        | 20.9998 | 11815 | 0.3713          |
| 0.3929        | 21.9987 | 12377 | 0.3720          |
| 0.3919        | 22.9993 | 12940 | 0.3736          |
| 0.3907        | 24.0    | 13503 | 0.3702          |
| 0.3893        | 24.9989 | 14065 | 0.3700          |
| 0.3894        | 25.9996 | 14628 | 0.3707          |
| 0.39          | 26.9984 | 15190 | 0.3687          |
| 0.3858        | 27.9991 | 15753 | 0.3712          |
| 0.3874        | 28.9998 | 16316 | 0.3669          |
| 0.3887        | 29.9987 | 16878 | 0.3685          |
| 0.3854        | 30.9993 | 17441 | 0.3670          |
| 0.3856        | 32.0    | 18004 | 0.3697          |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.4.0+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1