maguette9315's picture
End of training
ae9b08a verified
---
library_name: transformers
language:
- nl
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- maguette
model-index:
- name: SpeechT5 TTS MT V1
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 TTS MT V1
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the maguette dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7553
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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: 10
- training_steps: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| No log | 6.6667 | 10 | 1.0697 |
| No log | 13.3333 | 20 | 0.9269 |
| 1.1237 | 20.0 | 30 | 0.8719 |
| 1.1237 | 26.6667 | 40 | 0.8235 |
| 0.8225 | 33.3333 | 50 | 0.8047 |
| 0.8225 | 40.0 | 60 | 0.7953 |
| 0.8225 | 46.6667 | 70 | 0.7818 |
| 0.7747 | 53.3333 | 80 | 0.7663 |
| 0.7747 | 60.0 | 90 | 0.7559 |
| 0.7322 | 66.6667 | 100 | 0.7553 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.6.0+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3