---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ceb_b64_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_b64_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: 0.3930

## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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 |
|:-------------:|:--------:|:----:|:---------------:|
| 0.5525        | 19.6078  | 500  | 0.4686          |
| 0.4756        | 39.2157  | 1000 | 0.4276          |
| 0.4543        | 58.8235  | 1500 | 0.4116          |
| 0.4346        | 78.4314  | 2000 | 0.4028          |
| 0.4292        | 98.0392  | 2500 | 0.3997          |
| 0.4166        | 117.6471 | 3000 | 0.3952          |
| 0.4122        | 137.2549 | 3500 | 0.3957          |
| 0.4063        | 156.8627 | 4000 | 0.3940          |
| 0.4028        | 176.4706 | 4500 | 0.3951          |
| 0.3982        | 196.0784 | 5000 | 0.3931          |
| 0.4055        | 215.6863 | 5500 | 0.3946          |
| 0.4019        | 235.2941 | 6000 | 0.3925          |
| 0.4           | 254.9020 | 6500 | 0.3940          |
| 0.4046        | 274.5098 | 7000 | 0.3953          |
| 0.3955        | 294.1176 | 7500 | 0.3945          |
| 0.3944        | 313.7255 | 8000 | 0.3930          |


### Framework versions

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