---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b32_le4_s8000
  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. -->

# ceb_b32_le4_s8000

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: 0.3991

## 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: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4691        | 9.9010   | 500  | 0.4229          |
| 0.4352        | 19.8020  | 1000 | 0.4041          |
| 0.424         | 29.7030  | 1500 | 0.4032          |
| 0.4091        | 39.6040  | 2000 | 0.4037          |
| 0.4032        | 49.5050  | 2500 | 0.3995          |
| 0.3877        | 59.4059  | 3000 | 0.4005          |
| 0.3794        | 69.3069  | 3500 | 0.3979          |
| 0.3755        | 79.2079  | 4000 | 0.4074          |
| 0.3694        | 89.1089  | 4500 | 0.3979          |
| 0.3559        | 99.0099  | 5000 | 0.4004          |
| 0.3633        | 108.9109 | 5500 | 0.4046          |
| 0.3557        | 118.8119 | 6000 | 0.3987          |
| 0.3548        | 128.7129 | 6500 | 0.3986          |
| 0.3465        | 138.6139 | 7000 | 0.3982          |
| 0.3403        | 148.5149 | 7500 | 0.4006          |
| 0.34          | 158.4158 | 8000 | 0.3991          |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1