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---
license: mit
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
model-index:
- name: speecht5_finetuned_mozilla_foundation_common_voice_13_german
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_mozilla_foundation_common_voice_13_german
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co./microsoft/speecht5_tts) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4527
## 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: 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
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 0.5165 | 1.0 | 2193 | 0.4883 |
| 0.5125 | 2.0 | 4387 | 0.4789 |
| 0.4985 | 3.0 | 6580 | 0.4727 |
| 0.4963 | 4.0 | 8774 | 0.4701 |
| 0.4901 | 5.0 | 10967 | 0.4656 |
| 0.4814 | 6.0 | 13161 | 0.4611 |
| 0.4822 | 7.0 | 15354 | 0.4588 |
| 0.48 | 8.0 | 17548 | 0.4607 |
| 0.4676 | 9.0 | 19741 | 0.4564 |
| 0.4665 | 10.0 | 21935 | 0.4558 |
| 0.4652 | 11.0 | 24128 | 0.4549 |
| 0.4615 | 12.0 | 26322 | 0.4536 |
| 0.4716 | 13.0 | 28515 | 0.4541 |
| 0.462 | 14.0 | 30709 | 0.4526 |
| 0.4666 | 15.0 | 32902 | 0.4521 |
| 0.4591 | 16.0 | 35096 | 0.4532 |
| 0.4608 | 17.0 | 37289 | 0.4522 |
| 0.4605 | 18.0 | 39483 | 0.4513 |
| 0.4588 | 19.0 | 41676 | 0.4530 |
| 0.4561 | 20.0 | 43860 | 0.4527 |
### Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3