---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- doof-ferb/infore1_25hours
model-index:
- name: speecht5_finetuned_infore1_25hours
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_infore1_25hours

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the doof-ferb/infore1_25hours dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4221

## 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: 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4904        | 2.3761 | 1000 | 0.4506          |
| 0.4656        | 4.7522 | 2000 | 0.4351          |
| 0.4594        | 7.1262 | 3000 | 0.4258          |
| 0.458         | 9.5022 | 4000 | 0.4221          |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0