---
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: 0.4479

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 5.7875        | 0.1791 | 50   | 0.6062          |
| 4.5876        | 0.3583 | 100  | 0.5088          |
| 4.4072        | 0.5374 | 150  | 0.4908          |
| 4.3177        | 0.7165 | 200  | 0.4883          |
| 4.1852        | 0.8957 | 250  | 0.4808          |
| 4.1009        | 1.0748 | 300  | 0.4691          |
| 4.0833        | 1.2539 | 350  | 0.4677          |
| 4.0461        | 1.4330 | 400  | 0.4643          |
| 4.0024        | 1.6122 | 450  | 0.4587          |
| 3.9729        | 1.7913 | 500  | 0.4593          |
| 3.9057        | 1.9704 | 550  | 0.4555          |
| 3.8765        | 2.1496 | 600  | 0.4567          |
| 3.9148        | 2.3287 | 650  | 0.4541          |
| 3.8446        | 2.5078 | 700  | 0.4503          |
| 3.8321        | 2.6870 | 750  | 0.4511          |
| 3.8683        | 2.8661 | 800  | 0.4479          |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1