---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b64_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_b64_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: 0.4050

## 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: 4
- total_train_batch_size: 64
- 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 |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4561        | 19.8020  | 500  | 0.4151          |
| 0.4179        | 39.6040  | 1000 | 0.3994          |
| 0.4075        | 59.4059  | 1500 | 0.4018          |
| 0.3981        | 79.2079  | 2000 | 0.4029          |
| 0.3862        | 99.0099  | 2500 | 0.3978          |
| 0.3726        | 118.8119 | 3000 | 0.3978          |
| 0.365         | 138.6139 | 3500 | 0.3960          |
| 0.3525        | 158.4158 | 4000 | 0.3969          |
| 0.3545        | 178.2178 | 4500 | 0.3982          |
| 0.3473        | 198.0198 | 5000 | 0.4039          |
| 0.3439        | 217.8218 | 5500 | 0.4020          |
| 0.3371        | 237.6238 | 6000 | 0.4044          |
| 0.3362        | 257.4257 | 6500 | 0.4041          |
| 0.3311        | 277.2277 | 7000 | 0.4022          |
| 0.3345        | 297.0297 | 7500 | 0.4051          |
| 0.3348        | 316.8317 | 8000 | 0.4050          |


### Framework versions

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