---
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
- text-to-speech
datasets:
- speechbrain/spkrec-xvect-voxceleb
model-index:
- name: speecht5_finetuned_voxpopuli_en
  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_voxpopuli_en

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the speechbrain/spkrec-xvect-voxceleb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4466

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- 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: 1500
- training_steps: 12000

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5271        | 1.58  | 1000  | 0.4843          |
| 0.5025        | 3.15  | 2000  | 0.4648          |
| 0.4947        | 4.73  | 3000  | 0.4575          |
| 0.4857        | 6.3   | 4000  | 0.4543          |
| 0.487         | 7.88  | 5000  | 0.4519          |
| 0.4804        | 9.46  | 6000  | 0.4494          |
| 0.4798        | 11.03 | 7000  | 0.4487          |
| 0.4813        | 12.61 | 8000  | 0.4478          |
| 0.4831        | 14.18 | 9000  | 0.4476          |
| 0.4751        | 15.76 | 10000 | 0.4468          |
| 0.4795        | 17.34 | 11000 | 0.4463          |
| 0.474         | 18.91 | 12000 | 0.4466          |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 1.13.1
- Datasets 2.13.1
- Tokenizers 0.13.2