---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: HopefulASR
  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. -->

# HopefulASR

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: 0.4022

## 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.4624        | 3.0769  | 100  | 0.4358          |
| 0.4523        | 6.1538  | 200  | 0.4288          |
| 0.4385        | 9.2308  | 300  | 0.4148          |
| 0.4288        | 12.3077 | 400  | 0.4126          |
| 0.4262        | 15.3846 | 500  | 0.4114          |
| 0.4236        | 18.4615 | 600  | 0.4128          |
| 0.416         | 21.5385 | 700  | 0.4105          |
| 0.4118        | 24.6154 | 800  | 0.4111          |
| 0.4091        | 27.6923 | 900  | 0.4074          |
| 0.4044        | 30.7692 | 1000 | 0.4085          |
| 0.4048        | 33.8462 | 1100 | 0.4080          |
| 0.402         | 36.9231 | 1200 | 0.4021          |
| 0.3957        | 40.0    | 1300 | 0.4034          |
| 0.3977        | 43.0769 | 1400 | 0.4027          |
| 0.3982        | 46.1538 | 1500 | 0.4041          |
| 0.395         | 49.2308 | 1600 | 0.4003          |
| 0.3913        | 52.3077 | 1700 | 0.4017          |
| 0.3969        | 55.3846 | 1800 | 0.4032          |
| 0.3918        | 58.4615 | 1900 | 0.4024          |
| 0.3898        | 61.5385 | 2000 | 0.4022          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1