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---
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
should probably proofread and complete it, then remove this comment. -->
# 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: 0.3692
## 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: 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:------:|:---------------:|
| 0.4445 | 1.0 | 9429 | 0.4100 |
| 0.4169 | 2.0 | 18858 | 0.3955 |
| 0.412 | 3.0 | 28287 | 0.3882 |
| 0.3982 | 4.0 | 37716 | 0.3826 |
| 0.4032 | 5.0 | 47145 | 0.3817 |
| 0.3951 | 6.0 | 56574 | 0.3782 |
| 0.3971 | 7.0 | 66003 | 0.3782 |
| 0.395 | 8.0 | 75432 | 0.3757 |
| 0.3952 | 9.0 | 84861 | 0.3749 |
| 0.3835 | 10.0 | 94290 | 0.3740 |
| 0.3863 | 11.0 | 103719 | 0.3754 |
| 0.3845 | 12.0 | 113148 | 0.3732 |
| 0.3788 | 13.0 | 122577 | 0.3715 |
| 0.3834 | 14.0 | 132006 | 0.3717 |
| 0.3894 | 15.0 | 141435 | 0.3718 |
| 0.3845 | 16.0 | 150864 | 0.3714 |
| 0.3823 | 17.0 | 160293 | 0.3692 |
| 0.3858 | 18.0 | 169722 | 0.3703 |
| 0.3919 | 19.0 | 179151 | 0.3716 |
| 0.3906 | 20.0 | 188580 | 0.3709 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|