---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_voice_dataset_bn_v_3
  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_3

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: 0.5008

## 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 |
|:-------------:|:--------:|:----:|:---------------:|
| 0.6046        | 12.2699  | 250  | 0.5646          |
| 0.5583        | 24.5399  | 500  | 0.5268          |
| 0.5364        | 36.8098  | 750  | 0.5188          |
| 0.5171        | 49.0798  | 1000 | 0.5087          |
| 0.5098        | 61.3497  | 1250 | 0.5018          |
| 0.501         | 73.6196  | 1500 | 0.5022          |
| 0.4984        | 85.8896  | 1750 | 0.4955          |
| 0.4929        | 98.1595  | 2000 | 0.5000          |
| 0.4933        | 110.4294 | 2250 | 0.4944          |
| 0.4868        | 122.6994 | 2500 | 0.5006          |
| 0.4805        | 134.9693 | 2750 | 0.4991          |
| 0.4802        | 147.2393 | 3000 | 0.5008          |


### Framework versions

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