---
language:
- da
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- alexandrainst/nst-da
model-index:
- name: speecht5_tts-finetuned-nst-da
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# speecht5_tts-finetuned-nst-da

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the NST Danish ASR Database dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3387
- Mae: 0.1486
- Mse: 0.0395
- Mcd: 16.3878
- Mae Rmcd: 0.1562

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Mae    | Mse    | Mcd     | Mae Rmcd |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:-------:|:--------:|
| 0.4202        | 1.0   | 2378  | 0.3851          | 0.1589 | 0.0446 | 17.5859 | 0.1674   |
| 0.3897        | 2.0   | 4756  | 0.3771          | 0.1578 | 0.0440 | 17.2975 | 0.1654   |
| 0.3749        | 3.0   | 7134  | 0.3636          | 0.1605 | 0.0450 | 17.3449 | 0.1670   |
| 0.359         | 4.0   | 9512  | 0.3632          | 0.1580 | 0.0443 | 17.2756 | 0.1654   |
| 0.3532        | 5.0   | 11890 | 0.3539          | 0.1592 | 0.0444 | 17.1294 | 0.1653   |
| 0.356         | 6.0   | 14268 | 0.3455          | 0.1536 | 0.0418 | 16.9892 | 0.1617   |
| 0.3437        | 7.0   | 16646 | 0.3426          | 0.1528 | 0.0416 | 16.8165 | 0.1605   |
| 0.3434        | 8.0   | 19024 | 0.3438          | 0.1534 | 0.0416 | 16.8859 | 0.1611   |
| 0.3391        | 9.0   | 21402 | 0.3487          | 0.1558 | 0.0429 | 16.7245 | 0.1615   |
| 0.3381        | 10.0  | 23780 | 0.3414          | 0.1516 | 0.0409 | 16.6136 | 0.1589   |
| 0.3455        | 11.0  | 26158 | 0.3395          | 0.1509 | 0.0406 | 16.6252 | 0.1586   |
| 0.3408        | 12.0  | 28536 | 0.3402          | 0.1504 | 0.0404 | 16.7043 | 0.1587   |
| 0.341         | 13.0  | 30914 | 0.3420          | 0.1527 | 0.0414 | 16.6290 | 0.1595   |
| 0.3279        | 14.0  | 33292 | 0.3388          | 0.1503 | 0.0404 | 16.5525 | 0.1579   |
| 0.328         | 15.0  | 35670 | 0.3389          | 0.1498 | 0.0401 | 16.4898 | 0.1574   |
| 0.3264        | 16.0  | 38048 | 0.3391          | 0.1497 | 0.0400 | 16.4882 | 0.1573   |
| 0.3318        | 17.0  | 40426 | 0.3383          | 0.1498 | 0.0402 | 16.5091 | 0.1575   |
| 0.3299        | 18.0  | 42804 | 0.3399          | 0.1492 | 0.0399 | 16.4604 | 0.1569   |
| 0.3304        | 19.0  | 45182 | 0.3399          | 0.1489 | 0.0396 | 16.4132 | 0.1565   |
| 0.3204        | 20.0  | 47560 | 0.3387          | 0.1486 | 0.0395 | 16.3878 | 0.1562   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2