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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- voxpopuli/fi
model-index:
- name: speecht5_finetuned_voxpopuli_fi_lim_speakrs
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_voxpopuli_fi_lim_speakrs
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the voxpopuli/fi dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4429
## 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: 10
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 8000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5587 | 1.25 | 500 | 0.4937 |
| 0.5176 | 2.5 | 1000 | 0.4703 |
| 0.4983 | 3.75 | 1500 | 0.4594 |
| 0.5016 | 5.0 | 2000 | 0.4584 |
| 0.4797 | 6.25 | 2500 | 0.4539 |
| 0.4845 | 7.5 | 3000 | 0.4512 |
| 0.4882 | 8.75 | 3500 | 0.4489 |
| 0.4721 | 10.0 | 4000 | 0.4469 |
| 0.4829 | 11.25 | 4500 | 0.4456 |
| 0.4974 | 12.5 | 5000 | 0.4457 |
| 0.4776 | 13.75 | 5500 | 0.4442 |
| 0.4866 | 15.0 | 6000 | 0.4441 |
| 0.4752 | 16.25 | 6500 | 0.4430 |
| 0.4765 | 17.5 | 7000 | 0.4430 |
| 0.4668 | 18.75 | 7500 | 0.4431 |
| 0.4823 | 20.0 | 8000 | 0.4429 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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