---
library_name: transformers
language:
- ar
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- speechbrain/spkrec-xvect-voxceleb
model-index:
- name: Speech 5
  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. -->

# Speech 5

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the Darija Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3400

## 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: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.2289        | 57.1429  | 100  | 0.3906          |
| 0.2089        | 114.2857 | 200  | 0.3636          |
| 0.1927        | 171.4286 | 300  | 0.3515          |
| 0.1855        | 228.5714 | 400  | 0.3444          |
| 0.1864        | 285.7143 | 500  | 0.3400          |


### Framework versions

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