---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b128_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_b128_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: 0.4096

## 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: 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: 2000
- training_steps: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4432        | 39.6040  | 500  | 0.4058          |
| 0.4129        | 79.2079  | 1000 | 0.3996          |
| 0.3992        | 118.8119 | 1500 | 0.3986          |
| 0.3814        | 158.4158 | 2000 | 0.3966          |
| 0.3688        | 198.0198 | 2500 | 0.4021          |
| 0.3574        | 237.6238 | 3000 | 0.4000          |
| 0.3482        | 277.2277 | 3500 | 0.3990          |
| 0.3421        | 316.8317 | 4000 | 0.4014          |
| 0.3414        | 356.4356 | 4500 | 0.4059          |
| 0.3328        | 396.0396 | 5000 | 0.4065          |
| 0.3277        | 435.6436 | 5500 | 0.4062          |
| 0.3248        | 475.2475 | 6000 | 0.4069          |
| 0.3245        | 514.8515 | 6500 | 0.4071          |
| 0.3219        | 554.4554 | 7000 | 0.4096          |
| 0.3227        | 594.0594 | 7500 | 0.4112          |
| 0.3191        | 633.6634 | 8000 | 0.4096          |


### Framework versions

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