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---
license: mit
base_model: microsoft/speecht5_vc
tags:
- generated_from_trainer
datasets:
- audiofolder
model-index:
- name: SpeechT5_finetuned_kha
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_kha
This model is a fine-tuned version of [microsoft/speecht5_vc](https://huggingface.co/microsoft/speecht5_vc) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4733
## 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: 3e-05
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 300
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.544 | 36.8664 | 1000 | 0.5145 |
| 0.5013 | 73.7327 | 2000 | 0.4800 |
| 0.4754 | 110.5991 | 3000 | 0.4705 |
| 0.4651 | 147.4654 | 4000 | 0.4710 |
| 0.456 | 184.3318 | 5000 | 0.4699 |
| 0.446 | 221.1982 | 6000 | 0.4702 |
| 0.443 | 258.0645 | 7000 | 0.4714 |
| 0.4437 | 294.9309 | 8000 | 0.4733 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.19.1