---
license: mit
base_model: miosipof/speecht5_tts_voxpopuli_it_v2
tags:
- generated_from_trainer
datasets:
- audiofolder
model-index:
- name: speecht5_tts_dysarthria_v1
  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_tts_dysarthria_v1

This model is a fine-tuned version of [miosipof/speecht5_tts_voxpopuli_it_v2](https://huggingface.co/miosipof/speecht5_tts_voxpopuli_it_v2) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5234

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 1.0113        | 0.7042  | 25   | 0.8442          |
| 0.8           | 1.4085  | 50   | 0.7084          |
| 0.7291        | 2.1127  | 75   | 0.6323          |
| 0.6698        | 2.8169  | 100  | 0.5875          |
| 0.6339        | 3.5211  | 125  | 0.5633          |
| 0.5747        | 4.2254  | 150  | 0.5552          |
| 0.5837        | 4.9296  | 175  | 0.5436          |
| 0.5882        | 5.6338  | 200  | 0.5417          |
| 0.5692        | 6.3380  | 225  | 0.5363          |
| 0.5577        | 7.0423  | 250  | 0.5340          |
| 0.5411        | 7.7465  | 275  | 0.5323          |
| 0.5551        | 8.4507  | 300  | 0.5301          |
| 0.5671        | 9.1549  | 325  | 0.5292          |
| 0.5313        | 9.8592  | 350  | 0.5254          |
| 0.5546        | 10.5634 | 375  | 0.5246          |
| 0.5283        | 11.2676 | 400  | 0.5231          |
| 0.5484        | 11.9718 | 425  | 0.5222          |
| 0.5251        | 12.6761 | 450  | 0.5222          |
| 0.5443        | 13.3803 | 475  | 0.5223          |
| 0.5357        | 14.0845 | 500  | 0.5234          |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.19.1