---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_mehdi_as_Multi_token
  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_mehdi_as_Multi_token

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: 0.4877

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.6154        | 3.5556  | 100  | 0.5500          |
| 0.5594        | 7.1111  | 200  | 0.5302          |
| 0.5378        | 10.6667 | 300  | 0.5179          |
| 0.5086        | 14.2222 | 400  | 0.4924          |
| 0.4923        | 17.7778 | 500  | 0.4855          |
| 0.4871        | 21.3333 | 600  | 0.4844          |
| 0.4791        | 24.8889 | 700  | 0.4809          |
| 0.4724        | 28.4444 | 800  | 0.4793          |
| 0.4609        | 32.0    | 900  | 0.4837          |
| 0.4583        | 35.5556 | 1000 | 0.4877          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3