---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli/fi
model-index:
- name: speecht5_finetuned_voxpopuli_fi_lim_speakrs
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_finetuned_voxpopuli_fi_lim_speakrs

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli/fi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4429

## 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: 10
- eval_batch_size: 2
- seed: 42
- 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: 250
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5587        | 1.25  | 500  | 0.4937          |
| 0.5176        | 2.5   | 1000 | 0.4703          |
| 0.4983        | 3.75  | 1500 | 0.4594          |
| 0.5016        | 5.0   | 2000 | 0.4584          |
| 0.4797        | 6.25  | 2500 | 0.4539          |
| 0.4845        | 7.5   | 3000 | 0.4512          |
| 0.4882        | 8.75  | 3500 | 0.4489          |
| 0.4721        | 10.0  | 4000 | 0.4469          |
| 0.4829        | 11.25 | 4500 | 0.4456          |
| 0.4974        | 12.5  | 5000 | 0.4457          |
| 0.4776        | 13.75 | 5500 | 0.4442          |
| 0.4866        | 15.0  | 6000 | 0.4441          |
| 0.4752        | 16.25 | 6500 | 0.4430          |
| 0.4765        | 17.5  | 7000 | 0.4430          |
| 0.4668        | 18.75 | 7500 | 0.4431          |
| 0.4823        | 20.0  | 8000 | 0.4429          |


### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3