---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_German_dataset
  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_finetuned_German_dataset

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: 0.4241

## 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: 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: 125
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5004        | 8.4567  | 500  | 0.4634          |
| 0.475         | 16.9133 | 1000 | 0.4414          |
| 0.4581        | 25.3700 | 1500 | 0.4318          |
| 0.4439        | 33.8266 | 2000 | 0.4268          |
| 0.4446        | 42.2833 | 2500 | 0.4266          |
| 0.4377        | 50.7400 | 3000 | 0.4288          |
| 0.4343        | 59.1966 | 3500 | 0.4296          |
| 0.4372        | 67.6533 | 4000 | 0.4282          |
| 0.4405        | 76.1099 | 4500 | 0.4282          |
| 0.4218        | 84.5666 | 5000 | 0.4241          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1