---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_eng_ashish
  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_eng_ashish

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7111

## 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: 1
- training_steps: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0602 | 1    | 0.7250          |
| 5.9911        | 0.1203 | 2    | 1.1100          |
| 5.9911        | 0.1805 | 3    | 0.8121          |
| 6.7456        | 0.2406 | 4    | 0.7525          |
| 6.7456        | 0.3008 | 5    | 0.7550          |
| 6.1898        | 0.3609 | 6    | 0.7549          |
| 6.1898        | 0.4211 | 7    | 0.7394          |
| 5.7588        | 0.4812 | 8    | 0.7304          |
| 5.7588        | 0.5414 | 9    | 0.7182          |
| 5.2002        | 0.6015 | 10   | 0.7111          |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0