---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_voice_dataset_bn_v_4
  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_voice_dataset_bn_v_4

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: 0.5560

## 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: 1e-05
- 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: 125
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.6302        | 12.1212  | 250  | 0.5979          |
| 0.5895        | 24.2424  | 500  | 0.5645          |
| 0.5658        | 36.3636  | 750  | 0.5638          |
| 0.5495        | 48.4848  | 1000 | 0.5609          |
| 0.5541        | 60.6061  | 1250 | 0.5443          |
| 0.5431        | 72.7273  | 1500 | 0.5522          |
| 0.5321        | 84.8485  | 1750 | 0.5406          |
| 0.5321        | 96.9697  | 2000 | 0.5515          |
| 0.5267        | 109.0909 | 2250 | 0.5674          |
| 0.5334        | 121.2121 | 2500 | 0.5607          |
| 0.5202        | 133.3333 | 2750 | 0.5586          |
| 0.52          | 145.4545 | 3000 | 0.5560          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1