---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_en16_lr0.0001
  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_en16_lr0.0001

This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4458

## 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: 16
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4951        | 21.6216  | 100  | 0.4042          |
| 0.3963        | 43.2432  | 200  | 0.3986          |
| 0.3703        | 64.8649  | 300  | 0.4202          |
| 0.357         | 86.4865  | 400  | 0.4268          |
| 0.3528        | 108.1081 | 500  | 0.4501          |
| 0.3419        | 129.7297 | 600  | 0.4367          |
| 0.3314        | 151.3514 | 700  | 0.4399          |
| 0.3205        | 172.9730 | 800  | 0.4376          |
| 0.3127        | 194.5946 | 900  | 0.4444          |
| 0.3096        | 216.2162 | 1000 | 0.4458          |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1