---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b32_le5_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_le5_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: 0.3928

## 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: 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 |
|:-------------:|:--------:|:----:|:---------------:|
| 0.5667        | 9.9010   | 500  | 0.4776          |
| 0.4838        | 19.8020  | 1000 | 0.4321          |
| 0.4604        | 29.7030  | 1500 | 0.4157          |
| 0.4373        | 39.6040  | 2000 | 0.4034          |
| 0.4359        | 49.5050  | 2500 | 0.4006          |
| 0.4236        | 59.4059  | 3000 | 0.3975          |
| 0.4196        | 69.3069  | 3500 | 0.3956          |
| 0.4183        | 79.2079  | 4000 | 0.3938          |
| 0.4148        | 89.1089  | 4500 | 0.3941          |
| 0.4034        | 99.0099  | 5000 | 0.3930          |
| 0.4137        | 108.9109 | 5500 | 0.3955          |
| 0.4094        | 118.8119 | 6000 | 0.3924          |
| 0.4112        | 128.7129 | 6500 | 0.3917          |
| 0.4041        | 138.6139 | 7000 | 0.3923          |
| 0.3989        | 148.5149 | 7500 | 0.3927          |
| 0.3989        | 158.4158 | 8000 | 0.3928          |


### Framework versions

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