---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: English_Technical_finetuned
  results: []
datasets:
- Tejasva-Maurya/English-Technical-Speech-Dataset
language:
- en
---

<!-- 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. -->

# English_Technical_finetuned

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an [English Technical Speech Dataset](https://huggingface.co/datasets/Tejasva-Maurya/English-Technical-Speech-Dataset) .
It achieves the following results on the evaluation set:
- Loss: 0.4451

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6122        | 0.3168 | 100  | 0.5289          |
| 0.5468        | 0.6337 | 200  | 0.4885          |
| 0.5207        | 0.9505 | 300  | 0.4745          |
| 0.5086        | 1.2673 | 400  | 0.4729          |
| 0.5012        | 1.5842 | 500  | 0.4638          |
| 0.4982        | 1.9010 | 600  | 0.4564          |
| 0.4888        | 2.2178 | 700  | 0.4528          |
| 0.4862        | 2.5347 | 800  | 0.4515          |
| 0.4866        | 2.8515 | 900  | 0.4454          |
| 0.4753        | 3.1683 | 1000 | 0.4451          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Tokenizers 0.19.1