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---
license: mit
base_model: microsoft/speecht5_tts
tags:
- text-to-speech
- generated_from_trainer
datasets:
- HeinrichWirth/example
model-index:
- name: speecht5_finetuned_nl_pet
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_nl_pet
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the HeinrichWirth/example dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4598
## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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: 500
- training_steps: 4000
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6583 | 1.08 | 250 | 0.5768 |
| 0.5507 | 2.15 | 500 | 0.5026 |
| 0.5254 | 3.23 | 750 | 0.4884 |
| 0.5199 | 4.3 | 1000 | 0.4806 |
| 0.51 | 5.38 | 1250 | 0.4743 |
| 0.5049 | 6.46 | 1500 | 0.4718 |
| 0.5001 | 7.53 | 1750 | 0.4686 |
| 0.5013 | 8.61 | 2000 | 0.4659 |
| 0.5003 | 9.68 | 2250 | 0.4653 |
| 0.5034 | 10.76 | 2500 | 0.4634 |
| 0.4922 | 11.83 | 2750 | 0.4633 |
| 0.4938 | 12.91 | 3000 | 0.4626 |
| 0.4905 | 13.99 | 3250 | 0.4605 |
| 0.489 | 15.06 | 3500 | 0.4624 |
| 0.4909 | 16.14 | 3750 | 0.4607 |
| 0.4904 | 17.21 | 4000 | 0.4598 |
### Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
|