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---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_k_voice_v3
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_k_voice_v3
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4215
## 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-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6081 | 0.2579 | 500 | 0.5853 |
| 0.5601 | 0.5159 | 1000 | 0.4924 |
| 0.5331 | 0.7738 | 1500 | 0.4709 |
| 0.5263 | 1.0317 | 2000 | 0.4698 |
| 0.5151 | 1.2897 | 2500 | 0.4615 |
| 0.5172 | 1.5476 | 3000 | 0.4618 |
| 0.5109 | 1.8055 | 3500 | 0.4486 |
| 0.5025 | 2.0635 | 4000 | 0.4461 |
| 0.4822 | 2.3214 | 4500 | 0.4356 |
| 0.4911 | 2.5793 | 5000 | 0.4439 |
| 0.4931 | 2.8372 | 5500 | 0.4331 |
| 0.4904 | 3.0952 | 6000 | 0.4304 |
| 0.474 | 3.3531 | 6500 | 0.4330 |
| 0.4716 | 3.6110 | 7000 | 0.4307 |
| 0.4673 | 3.8690 | 7500 | 0.4274 |
| 0.4654 | 4.1269 | 8000 | 0.4250 |
| 0.4609 | 4.3848 | 8500 | 0.4215 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.6.0
- Datasets 3.5.0
- Tokenizers 0.19.1
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