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---
library_name: transformers
language:
- en
license: mit
base_model: microsoft/speecht5_tts
tags:
- English
- generated_from_trainer
datasets:
- Yassmen/TTS_English_Technical_data
model-index:
- name: SpeechT5-fine-tune-en
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-fine-tune-en
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the TTS_English_Technical_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4504
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- 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: 100
- num_epochs: 3.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 4.6649 | 0.3583 | 100 | 0.5102 |
| 4.3456 | 0.7165 | 200 | 0.4964 |
| 4.1951 | 1.0748 | 300 | 0.4765 |
| 4.0516 | 1.4330 | 400 | 0.4654 |
| 3.9985 | 1.7913 | 500 | 0.4587 |
| 3.9263 | 2.1496 | 600 | 0.4546 |
| 3.91 | 2.5078 | 700 | 0.4505 |
| 3.8458 | 2.8661 | 800 | 0.4504 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1